Comparative Genome Annotation Research Articles

Annotation of a Newly Sequenced Genomic Region in Drosophila ananassae

Understanding evolutionary changes across Drosophila species can lead to a better understanding of how genomes have changed over time. Drosophila species have existed for millions of years, allowing the opportunity to study and identify the functions of genes orthologous to human genes. The etiology of numerous diseases can be better elucidated through the utilization of bioinformatic tools and genomic annotation. The Genome Education Partnership (GEP) is a nationwide community that provides undergraduate students the opportunity to gain experience in annotating eukaryotic genomes. Through the use of bioinformatics tools such as UCSC Genome Browser, NCBI Blast, and Flybase, students participate in the F‐element and Pathways projects. The F‐element project involves the annotation of protein‐coding genes located on chromosome four, commonly known as the Muller F element. Over time, the F element in some species of Drosophila, including Drosophila ananassae, has been expanding. Comparative genome annotation analyzing changes in the organization of this genomic region may lead to a better understanding of the complexity of these genomes. The Pathways project involves annotating specific genes involved in the Insulin Signaling Pathway. These genes play a critical role in the regulation of expression and metabolism in many eukaryotes. In this study, the annotation of a genomic region in Drosophila ananassae is discussed.A 25,000 base pair region of chromosome 3L in D. ananassae (Muller D element) was annotated for comparison to the F element. In this region, known as Contig 21, five protein‐coding genes were identified: CG10222, CG10713, CG32121, CG33263, and flr. These genes had high protein alignment (70% to 90% amino acid identity) compared to Drosophila melanogaster, however, the flr gene possessed some interesting characteristics. Upon the annotation of the flr gene in Drosophila ananassae, it was predicted that one of the isoforms was no longer expressed and/or functional. The gene flr encodes the Drosophila Actin Interacting Protein 1, which interacts with the gene product of trs (cofillin) to promote F‐actin disassembly. In Drosophila melanogaster, the flr gene encodes two isoforms, however in Drosophila ananassae, only the flr‐PA isoform appears to be expressed and/or functional. A deletion/insertion of a nucleotide within exon 1 in the flr gene leads to a frameshift resulting in a non‐functional protein due to a change in the original stop codon of isoform B in D. ananassae. The gene flr plays an important role in the development of the organism, therefore molecular analysis was utilized to confirm the annotation model above. RNA was extracted from Drosophila ananassae, and reverse transcription PCR (RT‐PCR) was utilized to amplify this region of the genome. Dideoxy sequencing was performed to analyze the expression of different isoforms of this gene. The sequencing data was compared to the Drosophila ananassae and Drosophila melanogaster genomes using BLAST and the UCSC Genome Browser. This data supported the expression of only one isoform of the flr gene in D. ananassae. This data also suggests that one of the flr gene isoforms is highly conserved in this species. Additional analysis of newly sequenced genomic data such as this will provide additional understanding on how genomes such as these have changed over time.

Insights into the Polyhydroxybutyrate Biosynthesis in Ralstonia solanacearum Using Parallel 13C Tracers and Comparative Genome Analysis.

Bacterial accumulation of poly(3-hydroxybutyrate) [P(3HB)] is a metabolic strategy often adopted to cope with challenging surroundings. Ralstonia solanacearum, a phytopathogen, seems to be an ideal candidate with inherent ability to accumulate this biodegradable polymer of high industrial relevance. This study is focused on investigating the metabolic networks that channel glucose into P(3HB) using comparative genome analysis, 13C tracers, microscopy, gas chromatography-mass spectrometry (GC-MS), and proton nuclear magnetic resonance (1H NMR). Comparative genome annotation of 87 R. solanacearum strains confirmed the presence of a conserved P(3HB) biosynthetic pathway genes in the chromosome. Parallel 13C glucose feeding ([1-13C], [1,2-13C]) analysis mapped the glucose oxidation to 3-hydroxybutyrate (3HB), the metabolic precursor of P(3HB) via the Entner-Doudoroff pathway (ED pathway), potentially to meet the NADPH demands. Fluorescence microscopy, GC-MS, and 1H NMR analysis further confirmed the ability of R. solanacearum to accumulate P(3HB) granules. In addition, it is demonstrated that the carbon/nitrogen (C/N) ratio influences the P(3HB) yields, thereby highlighting the need to further optimize the bioprocessing parameters. This study provided key insights into the biosynthetic abilities of R. solanacearum as a promising P(3HB) producer.

The Douglas-Fir Genome Sequence Reveals Specialization of the Photosynthetic Apparatus in Pinaceae.

A reference genome sequence for Pseudotsuga menziesii var. menziesii (Mirb.) Franco (Coastal Douglas-fir) is reported, thus providing a reference sequence for a third genus of the family Pinaceae. The contiguity and quality of the genome assembly far exceeds that of other conifer reference genome sequences (contig N50 = 44,136 bp and scaffold N50 = 340,704 bp). Incremental improvements in sequencing and assembly technologies are in part responsible for the higher quality reference genome, but it may also be due to a slightly lower exact repeat content in Douglas-fir vs. pine and spruce. Comparative genome annotation with angiosperm species reveals gene-family expansion and contraction in Douglas-fir and other conifers which may account for some of the major morphological and physiological differences between the two major plant groups. Notable differences in the size of the NDH-complex gene family and genes underlying the functional basis of shade tolerance/intolerance were observed. This reference genome sequence not only provides an important resource for Douglas-fir breeders and geneticists but also sheds additional light on the evolutionary processes that have led to the divergence of modern angiosperms from the more ancient gymnosperms.

ODG: Omics database generator - a tool for generating, querying, and analyzing multi-omics comparative databases to facilitate biological understanding

BackgroundRapid generation of omics data in recent years have resulted in vast amounts of disconnected datasets without systemic integration and knowledge building, while individual groups have made customized, annotated datasets available on the web with few ways to link them to in-lab datasets. With so many research groups generating their own data, the ability to relate it to the larger genomic and comparative genomic context is becoming increasingly crucial to make full use of the data.ResultsThe Omics Database Generator (ODG) allows users to create customized databases that utilize published genomics data integrated with experimental data which can be queried using a flexible graph database. When provided with omics and experimental data, ODG will create a comparative, multi-dimensional graph database. ODG can import definitions and annotations from other sources such as InterProScan, the Gene Ontology, ENZYME, UniPathway, and others. This annotation data can be especially useful for studying new or understudied species for which transcripts have only been predicted, and rapidly give additional layers of annotation to predicted genes. In better studied species, ODG can perform syntenic annotation translations or rapidly identify characteristics of a set of genes or nucleotide locations, such as hits from an association study. ODG provides a web-based user-interface for configuring the data import and for querying the database. Queries can also be run from the command-line and the database can be queried directly through programming language hooks available for most languages. ODG supports most common genomic formats as well as generic, easy to use tab-separated value format for user-provided annotations.ConclusionsODG is a user-friendly database generation and query tool that adapts to the supplied data to produce a comparative genomic database or multi-layered annotation database. ODG provides rapid comparative genomic annotation and is therefore particularly useful for non-model or understudied species. For species for which more data are available, ODG can be used to conduct complex multi-omics, pattern-matching queries.

Reduce Manual Curation by Combining Gene Predictions from Multiple Annotation Engines, a Case Study of Start Codon Prediction

Nowadays, prokaryotic genomes are sequenced faster than the capacity to manually curate gene annotations. Automated genome annotation engines provide users a straight-forward and complete solution for predicting ORF coordinates and function. For many labs, the use of AGEs is therefore essential to decrease the time necessary for annotating a given prokaryotic genome. However, it is not uncommon for AGEs to provide different and sometimes conflicting predictions. Combining multiple AGEs might allow for more accurate predictions. Here we analyzed the ab initio open reading frame (ORF) calling performance of different AGEs based on curated genome annotations of eight strains from different bacterial species with GC% ranging from 35–52%. We present a case study which demonstrates a novel way of comparative genome annotation, using combinations of AGEs in a pre-defined order (or path) to predict ORF start codons. The order of AGE combinations is from high to low specificity, where the specificity is based on the eight genome annotations. For each AGE combination we are able to derive a so-called projected confidence value, which is the average specificity of ORF start codon prediction based on the eight genomes. The projected confidence enables estimating likeliness of a correct prediction for a particular ORF start codon by a particular AGE combination, pinpointing ORFs notoriously difficult to predict start codons. We correctly predict start codons for 90.5±4.8% of the genes in a genome (based on the eight genomes) with an accuracy of 81.1±7.6%. Our consensus-path methodology allows a marked improvement over majority voting (9.7±4.4%) and with an optimal path ORF start prediction sensitivity is gained while maintaining a high specificity.

Sequencing and annotation of the Ophiostoma ulmigenome

BackgroundThe ascomycete fungus Ophiostoma ulmi was responsible for the initial pandemic of the massively destructive Dutch elm disease in Europe and North America in early 1910. Dutch elm disease has ravaged the elm tree population globally and is a major threat to the remaining elm population. O. ulmi is also associated with valuable biomaterials applications. It was recently discovered that proteins from O. ulmi can be used for efficient transformation of amylose in the production of bioplastics.ResultsWe have sequenced the 31.5 Mb genome of O.ulmi using Illumina next generation sequencing. Applying both de novo and comparative genome annotation methods, we predict a total of 8639 gene models. The quality of the predicted genes was validated using a variety of data sources consisting of EST data, mRNA-seq data and orthologs from related fungal species. Sequence-based computational methods were used to identify candidate virulence-related genes. Metabolic pathways were reconstructed and highlight specific enzymes that may play a role in virulence.ConclusionsThis genome sequence will be a useful resource for further research aimed at understanding the molecular mechanisms of pathogenicity by O. ulmi. It will also facilitate the identification of enzymes necessary for industrial biotransformation applications.

Comparative genomic analysis of the false killer whale (Pseudorca crassidens) LMBR1 locus

The sequencing and comparative genomic analysis of LMBR1 loci in mammals or other species, including human, would be very important in understanding evolutionary genetic changes underlying the evolution of limb development. In this regard, comparative genomic annotation of the false killer whale LMBR1 locus could shed new light on the evolution of limb development. We sequenced two false killer whale BAC clones, corresponding to 156 kb and 144 kb, respectively, harboring the tightly linked RNF32, LMBR1, and NOM1 genes. Our annotation of the false killer whale LMBR1 gene showed that it consists of 17 exons (1473 bp), in contrast to 18 exons (1596 bp) in human, and it displays 93.1% and 95.6% nucleotide and amino acid sequence similarity, respectively, compared with the human gene. In particular, we discovered that exon 10, deleted in the false killer whale LMBR1 gene, is present only in primates, and this fact strongly implies that exon 10 might be crucial in determining primate-specific limb development. ZRS and TFBS sequences have been well conserved across 11 species, suggesting that these regions could be involved in an important function of limb development and limb patterning. The neighboring gene RNF32 showed several lineage-conserved exons, such as exons 2 through 9 conserved in eutherian mammals, exons 3 through 9 conserved in mammals, and exons 5 through 9 conserved in vertebrates. The other neighboring gene, NOM1, had undergone a substitution (ATG→GTA) at the start codon, giving rise to a 36 bp shorter N-terminal sequence compared with the human sequence. Our comparative analysis of the false killer whale LMBR1 genomic locus provides important clues regarding the genetic regions that may play crucial roles in limb development and patterning.

Gene-oriented ortholog database: a functional comparison platform for orthologous loci

The accumulation of complete genomic sequences enhances the need for functional annotation. Associating existing functional annotation of orthologs can speed up the annotation process and even examine the existing annotation. However, current protein sequence-based ortholog databases provide ambiguous and incomplete orthology in eukaryotes. It is because that isoforms, derived by alternative splicing (AS), often share higher sequence similarity to interfere the sequence-based identification. Gene-Oriented Ortholog Database (GOOD) employs genomic locations of transcripts to cluster AS-derived isoforms prior to ortholog delineation to eliminate the interference from AS. From the gene-oriented presentation, isoforms can be clearly associated to their genes to provide comprehensive ortholog information and further be discriminated from paralogs. Aside from, displaying clusters of isoforms between orthologous genes can present the evolution variation at the transcription level. Based on orthology, GOOD additionally comprises functional annotation from the Gene Ontology (GO) database. However, there exist redundant annotations, both parent and child terms assigned to the same gene, in the GO database. It is difficult to precisely draw the numerical comparison of term counts between orthologous genes annotated with redundant terms. Instead of the description only, GOOD further provides the GO graphs to reveal hierarchical-like relationships among divergent functionalities. Therefore, the redundancy of GO terms can be examined, and the context among compared terms is more comprehensive. In sum, GOOD can improve the interpretation in the molecular function from experiments in the model organism and provide clear comparative genomic annotation across organisms.Database URL: http://goods.ibms.sinica.edu.tw/goods/

Toward the automated generation of genome-scale metabolic networks in the SEED

BackgroundCurrent methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process.ResultsWe have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis.ConclusionOur method sets the stage for the automated generation of substantially complete metabolic networks for over 400 complete genome sequences currently in the SEED. With each genome that is processed using our tools, the database of common components grows to cover more of the diversity of metabolic pathways. This increases the likelihood that components of reaction networks for subsequently processed genomes can be retrieved from the database, rather than assembled and verified manually.

The Ashbya Genome Database (AGD)--a tool for the yeast community and genome biologists

The Ashbya Genome Database (AGD) is a comprehensive online source of information covering genes from the filamentous fungus Ashbya gossypii. The database content is based upon comparative genome annotation between A.gossypii and the closely related budding yeast Saccharomyces cerevisiae taking both sequence similarity and synteny (conserved order and orientation) into account. Release 2 of AGD contains 4718 protein-encoding loci located across seven chromosomes. Information can be retrieved using systematic or standard locus names from A.gossypii as well as budding and fission yeast. Approximately 90% of the genes in the genome of A.gossypii are homologous and syntenic to loci of budding yeast. Therefore, AGD is a useful tool not only for the various yeast communities in general but also for biologists who are interested in evolutionary aspects of genome research and comparative genome annotation. The database provides scientists with a convenient graphical user interface that includes various locus search and genome browsing options, data download and export functionalities and numerous reciprocal links to external databases including SGD, MIPS, GeneDB, KEGG, GermOnline and Swiss-Prot/TrEMBL. AGD is accessible at http://agd.unibas.ch/.