Finding the Core-Genes of Chloroplasts

Due to the recent evolution of sequencing techniques, the number of available genomes is rising steadily, leading to the possibility to make large scale genomic comparison between sets of close species. An interesting question to answer is: what is the common functionality genes of a collection of species, or conversely, to determine what is specific to a given species when compared to other ones belonging in the same genus, family, etc. Investigating such problem means to find both core and pan genomes of a collection of species, \textit{i.e.}, genes in common to all the species vs. the set of all genes in all species under consideration. However, obtaining trustworthy core and pan genomes is not an easy task, leading to a large amount of computation, and requiring a rigorous methodology. Surprisingly, as far as we know, this methodology in finding core and pan genomes has not really been deeply investigated. This research work tries to fill this gap by focusing only on chloroplastic genomes, whose reasonable sizes allow a deep study. To achieve this goal, a collection of 99 chloroplasts are considered in this article. Two methodologies have been investigated, respectively based on sequence similarities and genes names taken from annotation tools. The obtained results will finally be evaluated in terms of biological relevance

An approach to describing and analysing bulk biological annotation quality: a case study using UniProtKB

Motivation: Annotations are a key feature of many biological databases, used to convey our knowledge of a sequence to the reader. Ideally, annotations are curated manually, however manual curation is costly, time consuming and requires expert knowledge and training. Given these issues and the exponential increase of data, many databases implement automated annotation pipelines in an attempt to avoid un-annotated entries. Both manual and automated annotations vary in quality between databases and annotators, making assessment of annotation reliability problematic for users. The community lacks a generic measure for determining annotation quality and correctness, which we look at addressing within this article. Specifically we investigate word reuse within bulk textual annotations and relate this to Zipf's Principle of Least Effort. We use UniProt Knowledge Base (UniProtKB) as a case study to demonstrate this approach since it allows us to compare annotation change, both over time and between automated and manually curated annotations. Results: By applying power-law distributions to word reuse in annotation, we show clear trends in UniProtKB over time, which are consistent with existing studies of quality on free text English. Further, we show a clear distinction between manual and automated analysis and investigate cohorts of protein records as they mature. These results suggest that this approach holds distinct promise as a mechanism for judging annotation quality. Availability: Source code is available at the authors website: http://homepages.cs.ncl.ac.uk/m.j.bell1/annotation. Contact: [email protected]: Paper accepted at The European Conference on Computational Biology 2012 (ECCB'12). Subsequently will be published in a special issue of the journal Bioinformatics. Paper consists of 8 pages, made up of 5 figure

Transcriptome survey of the anhydrobiotic tardigrade Milnesium tardigradum in comparison with Hypsibius dujardini and Richtersius coronifer

<p>Abstract</p> <p>Background</p> <p>The phenomenon of desiccation tolerance, also called anhydrobiosis, involves the ability of an organism to survive the loss of almost all cellular water without sustaining irreversible damage. Although there are several physiological, morphological and ecological studies on tardigrades, only limited DNA sequence information is available. Therefore, we explored the transcriptome in the active and anhydrobiotic state of the tardigrade <it>Milnesium tardigradum </it>which has extraordinary tolerance to desiccation and freezing. In this study, we present the first overview of the transcriptome of <it>M. tardigradum </it>and its response to desiccation and discuss potential parallels to stress responses in other organisms.</p> <p>Results</p> <p>We sequenced a total of 9984 expressed sequence tags (ESTs) from two cDNA libraries from the eutardigrade <it>M. tardigradum </it>in its active and inactive, anhydrobiotic (tun) stage. Assembly of these ESTs resulted in 3283 putative unique transcripts, whereof ~50% showed significant sequence similarity to known genes. The resulting unigenes were functionally annotated using the Gene Ontology (GO) vocabulary. A GO term enrichment analysis revealed several GOs that were significantly underrepresented in the inactive stage. Furthermore we compared the putative unigenes of <it>M. tardigradum </it>with ESTs from two other eutardigrade species that are available from public sequence databases, namely <it>Richtersius coronifer </it>and <it>Hypsibius dujardini</it>. The processed sequences of the three tardigrade species revealed similar functional content and the <it>M. tardigradum </it>dataset contained additional sequences from tardigrades not present in the other two.</p> <p>Conclusions</p> <p>This study describes novel sequence data from the tardigrade <it>M. tardigradum</it>, which significantly contributes to the available tardigrade sequence data and will help to establish this extraordinary tardigrade as a model for studying anhydrobiosis. Functional comparison of active and anhydrobiotic tardigrades revealed a differential distribution of Gene Ontology terms associated with chromatin structure and the translation machinery, which are underrepresented in the inactive animals. These findings imply a widespread metabolic response of the animals on dehydration. The collective tardigrade transcriptome data will serve as a reference for further studies and support the identification and characterization of genes involved in the anhydrobiotic response.</p

Salmo salar and Esox lucius full-length cDNA sequences reveal changes in evolutionary pressures on a post-tetraploidization genome

<p>Abstract</p> <p>Background</p> <p>Salmonids are one of the most intensely studied fish, in part due to their economic and environmental importance, and in part due to a recent whole genome duplication in the common ancestor of salmonids. This duplication greatly impacts species diversification, functional specialization, and adaptation. Extensive new genomic resources have recently become available for Atlantic salmon (<it>Salmo salar</it>), but documentation of allelic versus duplicate reference genes remains a major uncertainty in the complete characterization of its genome and its evolution.</p> <p>Results</p> <p>From existing expressed sequence tag (EST) resources and three new full-length cDNA libraries, 9,057 reference quality full-length gene insert clones were identified for Atlantic salmon. A further 1,365 reference full-length clones were annotated from 29,221 northern pike (<it>Esox lucius</it>) ESTs. Pairwise d_N/d_Scomparisons within each of 408 sets of duplicated salmon genes using northern pike as a diploid out-group show asymmetric relaxation of selection on salmon duplicates.</p> <p>Conclusions</p> <p>9,057 full-length reference genes were characterized in <it>S. salar </it>and can be used to identify alleles and gene family members. Comparisons of duplicated genes show that while purifying selection is the predominant force acting on both duplicates, consistent with retention of functionality in both copies, some relaxation of pressure on gene duplicates can be identified. In addition, there is evidence that evolution has acted asymmetrically on paralogs, allowing one of the pair to diverge at a faster rate.</p

Structure Modeling of All Identified G Protein–Coupled Receptors in the Human Genome

G protein–coupled receptors (GPCRs), encoded by about 5% of human genes, comprise the largest family of integral membrane proteins and act as cell surface receptors responsible for the transduction of endogenous signal into a cellular response. Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. To address this issue, we employ the recently developed threading assembly refinement (TASSER) method to generate structure predictions for all 907 putative GPCRs in the human genome. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately 820 predicted models should have the correct folds. The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures. This is due to GPCR fragments that are predominantly from extracellular or intracellular domains as well as database annotation errors. Our preliminary validation includes the automated modeling of bovine rhodopsin, the only solved GPCR in the Protein Data Bank. With homologous templates excluded, the final model built by TASSER has a global C(α) root-mean-squared deviation from native of 4.6 Å, with a root-mean-squared deviation in the transmembrane helix region of 2.1 Å. Models of several representative GPCRs are compared with mutagenesis and affinity labeling data, and consistent agreement is demonstrated. Structure clustering of the predicted models shows that GPCRs with similar structures tend to belong to a similar functional class even when their sequences are diverse. These results demonstrate the usefulness and robustness of the in silico models for GPCR functional analysis. All predicted GPCR models are freely available for noncommercial users on our Web site (http://www.bioinformatics.buffalo.edu/GPCR)

Comparative Genomic and Transcriptomic Characterization of the Toxigenic Marine Dinoflagellate Alexandrium ostenfeldii

Many dinoflagellate species are notorious for the toxins they produce and ecological and human health consequences associated with harmful algal blooms (HABs). Dinoflagellates are particularly refractory to genomic analysis due to the enormous genome size, lack of knowledge about their DNA composition and structure, and peculiarities of gene regulation, such as spliced leader (SL) trans-splicing and mRNA transposition mechanisms. Alexandrium ostenfeldii is known to produce macrocyclic imine toxins, described as spirolides. We characterized the genome of A. ostenfeldii using a combination of transcriptomic data and random genomic clones for comparison with other dinoflagellates, particularly Alexandrium species. Examination of SL sequences revealed similar features as in other dinoflagellates, including Alexandrium species. SL sequences in decay indicate frequent retro-transposition of mRNA species. This probably contributes to overall genome complexity by generating additional gene copies. Sequencing of several thousand fosmid and bacterial artificial chromosome (BAC) ends yielded a wealth of simple repeats and tandemly repeated longer sequence stretches which we estimated to comprise more than half of the whole genome. Surprisingly, the repeats comprise a very limited set of 79–97 bp sequences; in part the genome is thus a relatively uniform sequence space interrupted by coding sequences. Our genomic sequence survey (GSS) represents the largest genomic data set of a dinoflagellate to date. Alexandrium ostenfeldii is a typical dinoflagellate with respect to its transcriptome and mRNA transposition but demonstrates Alexandrium-like stop codon usage. The large portion of repetitive sequences and the organization within the genome is in agreement with several other studies on dinoflagellates using different approaches. It remains to be determined whether this unusual composition is directly correlated to the exceptionally genome organization of dinoflagellates with a low amount of histones and histone-like proteins

Statistical and machine learning methods to study human CD4+ T cell proteome profiles

Mass spectrometry proteomics has become an important part of modern immunology, making major contributions to understanding protein expression levels, subcellular localizations, posttranslational modifications, and interactions in various immune cell populations. New developments in both experimental and computational techniques offer increasing opportunities for exploring the immune system and the molecular mechanisms involved in immune responses. Here, we focus on current computational approaches to infer relevant information from large mass spectrometry based protein profiling datasets, covering the different steps of the analysis from protein identification and quantification to further mining and modelling of the protein abundance data. Additionally, we provide a summary of the key proteome profiling studies on human CD4+ T cells and their different subtypes in health and disease