Annotation Of Eukaryotic Genomes Research Articles

G-OnRamp: a Galaxy-based platform for collaborative annotation of eukaryotic genomes.

SummaryG-OnRamp provides a user-friendly, web-based platform for collaborative, end-to-end annotation of eukaryotic genomes using UCSC Assembly Hubs and JBrowse/Apollo genome browsers with evidence tracks derived from sequence alignments, ab initio gene predictors, RNA-Seq data and repeat finders. G-OnRamp can be used to visualize large genomics datasets and to perform collaborative genome annotation projects in both research and educational settings.Availability and implementationThe virtual machine images and tutorials are available on the G-OnRamp web site (http://g-onramp.org/deployments). The source code is available under an Academic Free License version 3.0 through the goeckslab GitHub repository (https://github.com/goeckslab).Supplementary information Supplementary data are available at Bioinformatics online.

VAPiD: a lightweight cross-platform viral annotation pipeline and identification tool to facilitate virus genome submissions to NCBI GenBank

BackgroundWith sequencing technologies becoming cheaper and easier to use, more groups are able to obtain whole genome sequences of viruses of public health and scientific importance. Submission of genomic data to NCBI GenBank is a requirement prior to publication and plays a critical role in making scientific data publicly available. GenBank currently has automatic prokaryotic and eukaryotic genome annotation pipelines but has no viral annotation pipeline beyond influenza virus. Annotation and submission of viral genome sequence is a non-trivial task, especially for groups that do not routinely interact with GenBank for data submissions.ResultsWe present Viral Annotation Pipeline and iDentification (VAPiD), a portable and lightweight command-line tool for annotation and GenBank deposition of viral genomes. VAPiD supports annotation of nearly all unsegmented viral genomes. The pipeline has been validated on human immunodeficiency virus, human parainfluenza virus 1–4, human metapneumovirus, human coronaviruses (229E/OC43/NL63/HKU1/SARS/MERS), human enteroviruses/rhinoviruses, measles virus, mumps virus, Hepatitis A-E Virus, Chikungunya virus, dengue virus, and West Nile virus, as well the human polyomaviruses BK/JC/MCV, human adenoviruses, and human papillomaviruses. The program can handle individual or batch submissions of different viruses to GenBank and correctly annotates multiple viruses, including those that contain ribosomal slippage or RNA editing without prior knowledge of the virus to be annotated. VAPiD is programmed in Python and is compatible with Windows, Linux, and Mac OS systems.ConclusionsWe have created a portable, lightweight, user-friendly, internet-enabled, open-source, command-line genome annotation and submission package to facilitate virus genome submissions to NCBI GenBank. Instructions for downloading and installing VAPiD can be found at https://github.com/rcs333/VAPiD.

Peptimapper: proteogenomics workflow for the expert annotation of eukaryotic genomes

BackgroundAccurate structural annotation of genomes is still a challenge, despite the progress made over the past decade. The prediction of gene structure remains difficult, especially for eukaryotic species, and is often erroneous and incomplete. We used a proteogenomics strategy, taking advantage of the combination of proteomics datasets and bioinformatics tools, to identify novel protein coding-genes and splice isoforms, assign correct start sites, and validate predicted exons and genes.ResultsOur proteogenomics workflow, Peptimapper, was applied to the genome annotation of Ectocarpus sp., a key reference genome for both the brown algal lineage and stramenopiles. We generated proteomics data from various life cycle stages of Ectocarpus sp. strains and sub-cellular fractions using a shotgun approach. First, we directly generated peptide sequence tags (PSTs) from the proteomics data. Second, we mapped PSTs onto the translated genomic sequence. Closely located hits (i.e., PSTs locations on the genome) were then clustered to detect potential coding regions based on parameters optimized for the organism. Third, we evaluated each cluster and compared it to gene predictions from existing conventional genome annotation approaches. Finally, we integrated cluster locations into GFF files to use a genome viewer. We identified two potential novel genes, a ribosomal protein L22 and an aryl sulfotransferase and corrected the gene structure of a dihydrolipoamide acetyltransferase. We experimentally validated the results by RT-PCR and using transcriptomics data.ConclusionsPeptimapper is a complementary tool for the expert annotation of genomes. It is suitable for any organism and is distributed through a Docker image available on two public bioinformatics docker repositories: Docker Hub and BioShaDock. This workflow is also accessible through the Galaxy framework and for use by non-computer scientists at https://galaxy.protim.eu.Data are available via ProteomeXchange under identifier PXD010618.

Long-Read Annotation: Automated Eukaryotic Genome Annotation Based on Long-Read cDNA Sequencing.

Single-molecule full-length complementary DNA (cDNA) sequencing can aid genome annotation by revealing transcript structure and alternative splice forms, yet current annotation pipelines do not incorporate such information. Here we present long-read annotation (LoReAn) software, an automated annotation pipeline utilizing short- and long-read cDNA sequencing, protein evidence, and ab initio prediction to generate accurate genome annotations. Based on annotations of two fungal genomes (Verticillium dahliae and Plicaturopsis crispa) and two plant genomes (Arabidopsis [Arabidopsis thaliana] and Oryza sativa), we show that LoReAn outperforms popular annotation pipelines by integrating single-molecule cDNA-sequencing data generated from either the Pacific Biosciences or MinION sequencing platforms, correctly predicting gene structure, and capturing genes missed by other annotation pipelines.

Improving eukaryotic genome annotation using single molecule mRNA sequencing

BackgroundThe advantages of Pacific Biosciences (PacBio) single-molecule real-time (SMRT) technology include long reads, low systematic bias, and high consensus read accuracy. Here we use these attributes to improve on the genome annotation of the parasitic hookworm Ancylostoma ceylanicum using PacBio RNA-Seq.ResultsWe sequenced 192,888 circular consensus sequences (CCS) derived from cDNAs generated using the CloneTech SMARTer system. These SMARTer-SMRT libraries were normalized and size-selected providing a robust population of expressed structural genes for subsequent genome annotation. We demonstrate PacBio mRNA sequences based genome annotation improvement, compared to genome annotation using conventional sequencing-by-synthesis alone, by identifying 1609 (9.2%) new genes, extended the length of 3965 (26.7%) genes and increased the total genomic exon length by 1.9 Mb (12.4%). Non-coding sequence representation (primarily from UTRs based on dT reverse transcription priming) was particularly improved, increasing in total length by fifteen-fold, by increasing both the length and number of UTR exons. In addition, the UTR data provided by these CCS allowed for the identification of a novel SL2 splice leader sequence for A. ceylanicum and an increase in the number and proportion of functionally annotated genes. RNA-seq data also confirmed some of the newly annotated genes and gene features.ConclusionOverall, PacBio data has supported a significant improvement in gene annotation in this genome, and is an appealing alternative or complementary technique for genome annotation to the other transcript sequencing technologies.

Proteogenomic Tools and Approaches to Explore Protein Coding Landscapes of Eukaryotic Genomes.

Proteogenomic strategies aim to refine genome-wide annotations of protein coding features by using actual protein level observations. Most of the currently applied proteogenomic approaches include integrative analysis of multiple types of high-throughput omics data, e.g., genomics, transcriptomics, proteomics, etc. Recent efforts towards creating a human proteome map were primarily targeted to experimentally detect at least one protein product for each gene in the genome and extensively utilized proteogenomic approaches. The 14 year long wait to get a draft human proteome map, after completion of similar efforts to sequence the genome, explains the huge complexity and technical hurdles of such efforts. Further, the integrative analysis of large-scale multi-omics datasets inherent to these studies becomes a major bottleneck to their success. However, recent developments of various analysis tools and pipelines dedicated to proteogenomics reduce both the time and complexity of such analysis. Here, we summarize notable approaches, studies, software developments and their potential applications towards eukaryotic genome annotation and clinical proteogenomics.

Filling annotation gaps in yeast genomes using genome-wide contact maps

De novo sequencing of genomes is followed by annotation analyses aiming at identifying functional genomic features such as genes, non-coding RNAs or regulatory sequences, taking advantage of diverse datasets. These steps sometimes fail at detecting non-coding functional sequences: for example, origins of replication, centromeres and rDNA positions have proven difficult to annotate with high confidence. Here, we demonstrate an unconventional application of Chromosome Conformation Capture (3C) technique, which typically aims at deciphering the average 3D organization of genomes, by showing how functional information about the sequence can be extracted solely from the chromosome contact map. Specifically, we describe a combined experimental and bioinformatic procedure that determines the genomic positions of centromeres and ribosomal DNA clusters in yeasts, including species where classical computational approaches fail. For instance, we determined the centromere positions in Naumovozyma castellii, where these coordinates could not be obtained previously. Although computed centromere positions were characterized by conserved synteny with neighboring species, no consensus sequences could be found, suggesting that centromeric binding proteins or mechanisms have significantly diverged. We also used our approach to refine centromere positions in Kuraishia capsulata and to identify rDNA positions in Debaryomyces hansenii. Our study demonstrates how 3C data can be used to complete the functional annotation of eukaryotic genomes. The source code is provided in the Supplementary Material. This includes a zipped file with the Python code and a contact matrix of Saccharomyces cerevisiae. romain.koszul@pasteur.fr Supplementary data are available at Bioinformatics online.

RefSeq: an update on mammalian reference sequences

The National Center for Biotechnology Information (NCBI) Reference Sequence (RefSeq) database is a collection of annotated genomic, transcript and protein sequence records derived from data in public sequence archives and from computation, curation and collaboration (http://www.ncbi.nlm.nih.gov/refseq/). We report here on growth of the mammalian and human subsets, changes to NCBI’s eukaryotic annotation pipeline and modifications affecting transcript and protein records. Recent changes to NCBI’s eukaryotic genome annotation pipeline provide higher throughput, and the addition of RNAseq data to the pipeline results in a significant expansion of the number of transcripts and novel exons annotated on mammalian RefSeq genomes. Recent annotation changes include reporting supporting evidence for transcript records, modification of exon feature annotation and the addition of a structured report of gene and sequence attributes of biological interest. We also describe a revised protein annotation policy for alternatively spliced transcripts with more divergent predicted proteins and we summarize the current status of the RefSeqGene project.

Kinannote, a computer program to identify and classify members of the eukaryotic protein kinase superfamily

Motivation: Kinases of the eukaryotic protein kinase superfamily are key regulators of most aspects eukaryotic cellular behavior and have provided several drug targets including kinases dysregulated in cancers. The rapid increase in the number of genomic sequences has created an acute need to identify and classify members of this important class of enzymes efficiently and accurately.Results: Kinannote produces a draft kinome and comparative analyses for a predicted proteome using a single line command, and it is currently the only tool that automatically classifies protein kinases using the controlled vocabulary of Hanks and Hunter [Hanks and Hunter (1995)]. A hidden Markov model in combination with a position-specific scoring matrix is used by Kinannote to identify kinases, which are subsequently classified using a BLAST comparison with a local version of KinBase, the curated protein kinase dataset from www.kinase.com. Kinannote was tested on the predicted proteomes from four divergent species. The average sensitivity and precision for kinome retrieval from the test species are 94.4 and 96.8%. The ability of Kinannote to classify identified kinases was also evaluated, and the average sensitivity and precision for full classification of conserved kinases are 71.5 and 82.5%, respectively. Kinannote has had a significant impact on eukaryotic genome annotation, providing protein kinase annotations for 36 genomes made public by the Broad Institute in the period spanning 2009 to the present.Availability: Kinannote is freely available at http://sourceforge.net/projects/kinannote.Contact: jmgold@broadinstitute.orgSupplementary information: Supplementary data are available at Bioinformatics online.

NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy

The National Center for Biotechnology Information (NCBI) Reference Sequence (RefSeq) database is a collection of genomic, transcript and protein sequence records. These records are selected and curated from public sequence archives and represent a significant reduction in redundancy compared to the volume of data archived by the International Nucleotide Sequence Database Collaboration. The database includes over 16 000 organisms, 2.4 × 106 genomic records, 13 × 106 proteins and 2 × 106 RNA records spanning prokaryotes, eukaryotes and viruses (RefSeq release 49, September 2011). The RefSeq database is maintained by a combined approach of automated analyses, collaboration and manual curation to generate an up-to-date representation of the sequence, its features, names and cross-links to related sources of information. We report here on recent growth, the status of curating the human RefSeq data set, more extensive feature annotation and current policy for eukaryotic genome annotation via the NCBI annotation pipeline. More information about the resource is available online (see http://www.ncbi.nlm.nih.gov/RefSeq/).

Approaches to Fungal Genome Annotation

Fungal genome annotation is the starting point for analysis of genome content. This generally involves the application of diverse methods to identify features on a genome assembly such as protein-coding and non-coding genes, repeats and transposable elements, and pseudogenes. Here, we describe tools and methods leveraged for eukaryotic genome annotation with a focus on the annotation of fungal nuclear and mitochondrial genomes. We highlight the application of the latest technologies and tools to improve the quality of predicted gene sets. The Broad Institute eukaryotic genome annotation pipeline is described as one example of how such methods and tools are integrated into a sequencing center's production genome annotation environment.

Splicing signals in the human hemoglobin genes at the sequence and folding levels

Identification of the splice sites is a critical and tough issue in eukaryotic genome annotation. Here, a statistical study is introduced for detecting the splicing signals in the human hemoglobin (Hb) pre-mRNAs by using the approaches of regional pairwise alignment, splicing weight matrix scoring, and dynamic extended folding. First, the regional pairwise alignment results show that the coding regions of the human Hb genes are at a high level for both conservation and fluctuation. Second, the weighted matrix scoring results indicate that, although the authentic splicing motifs are always scored the highest in a sequence, the sequence motif alone is inadequate to precisely define the splice sites. Finally, we deduce the RNA frame structures by applying an extended folding approach to analyze the stable folding elements. We find out that the splice sequences tend to take stretching and partially paired conformations, which benefit recognition and competitive binding of the splicing factors. These results indicate that precise splicing is an integrated effect of multiple mechanisms of signal recognition at the level of sequence and structure.

Relationship of oxidative stress and endothelial dysfunction in sleep apnoea

The aim of the present study was to evaluate ischaemic reactive hyperaemia (IRH) in obstructive sleep apnoea (OSA) and its relationship with oxidative stress. We studied 69 consecutive patients referred to our Sleep Unit (Reina Sofia University Hospital, Cordoba, Spain). Patients with chronic diseases or those taking medication were excluded. IRH was assessed before and after polysomnography. Morning IRH and oxidative stress markers were compared between patients with (apnoea-hypopnoea index (AHI) ≥ 5) and without (AHI < 5) OSA. Measurements were repeated in 25 severe OSA patients after continuous positive airway pressure (CPAP) therapy. We included 46 OSA patients (mean ± sd AHI 49 ± 32.1) and 23 non-OSA subjects (AHI 3 ± 0.9). The OSA patients showed a significant worsening of morning IRH, and a significant increase in malondialdehyde and 8-hydroxydeoxyguanosine levels. Only the oxygen desaturation index independently explained morning IRH, while malondialdehyde levels showed a weak effect on IRH. In severe OSA patients, IRH improved significantly after CPAP treatment, as did malondialdehyde, 8-hydroxydeoxyguanosine and protein carbonyl levels. In OSA patients, endothelial dysfunction and oxidative stress were observed, and IRH worsened after sleep. The increase in oxidative stress was not associated with IRH, while intermittent hypoxia was strongly associated with IRH. In severe OSA patients, CPAP treatment improved oxidative stress and endothelial function.

The 2008 update of the Aspergillus nidulans genome annotation: A community effort

The identification and annotation of protein-coding genes is one of the primary goals of whole-genome sequencing projects, and the accuracy of predicting the primary protein products of gene expression is vital to the interpretation of the available data and the design of downstream functional applications. Nevertheless, the comprehensive annotation of eukaryotic genomes remains a considerable challenge. Many genomes submitted to public databases, including those of major model organisms, contain significant numbers of wrong and incomplete gene predictions. We present a community-based reannotation of the Aspergillus nidulans genome with the primary goal of increasing the number and quality of protein functional assignments through the careful review of experts in the field of fungal biology.

Splign: algorithms for computing spliced alignments with identification of paralogs

BackgroundThe computation of accurate alignments of cDNA sequences against a genome is at the foundation of modern genome annotation pipelines. Several factors such as presence of paralogs, small exons, non-consensus splice signals, sequencing errors and polymorphic sites pose recognized difficulties to existing spliced alignment algorithms.ResultsWe describe a set of algorithms behind a tool called Splign for computing cDNA-to-Genome alignments. The algorithms include a high-performance preliminary alignment, a compartment identification based on a formally defined model of adjacent duplicated regions, and a refined sequence alignment. In a series of tests, Splign has produced more accurate results than other tools commonly used to compute spliced alignments, in a reasonable amount of time.ConclusionSplign's ability to deal with various issues complicating the spliced alignment problem makes it a helpful tool in eukaryotic genome annotation processes and alternative splicing studies. Its performance is enough to align the largest currently available pools of cDNA data such as the human EST set on a moderate-sized computing cluster in a matter of hours. The duplications identification (compartmentization) algorithm can be used independently in other areas such as the study of pseudogenes.ReviewersThis article was reviewed by: Steven Salzberg, Arcady Mushegian and Andrey Mironov (nominated by Mikhail Gelfand).

EAnnot: A genome annotation tool using experimental evidence

The sequence of any genome becomes most useful for biological experimentation when a complete and accurate gene set is available. Gene prediction programs offer an efficient way to generate an automated gene set. Manual annotation, when performed by experienced annotators, is more accurate and complete than automated annotation. However, it is a laborious and expensive process, and by its nature, introduces a degree of variability not found with automated annotation. EAnnot (Electronic Annotation) is a program originally developed for manually annotating the human genome. It combines the latest bioinformatics tools to extract and analyze a wide range of publicly available data in order to achieve fast and reliable automatic gene prediction and annotation. EAnnot builds gene models based on mRNA, EST, and protein alignments to genomic sequence, attaches supporting evidence to the corresponding genes, identifies pseudogenes, and locates poly(A) sites and signals. Here, we compare manual annotation of human chromosome 6 with annotation performed by EAnnot in order to assess the latter's accuracy. EAnnot can readily be applied to manual annotation of other eukaryotic genomes and can be used to rapidly obtain an automated gene set.

Full-length messenger RNA sequences greatly improve genome annotation.

Annotation of eukaryotic genomes is a complex endeavor that requires the integration of evidence from multiple, often contradictory, sources. With the ever-increasing amount of genome sequence data now available, methods for accurate identification of large numbers of genes have become urgently needed. In an effort to create a set of very high-quality gene models, we used the sequence of 5,000 full-length gene transcripts from Arabidopsis to re-annotate its genome. We have mapped these transcripts to their exact chromosomal locations and, using alignment programs, have created gene models that provide a reference set for this organism. Approximately 35% of the transcripts indicated that previously annotated genes needed modification, and 5% of the transcripts represented newly discovered genes. We also discovered that multiple transcription initiation sites appear to be much more common than previously known, and we report numerous cases of alternative mRNA splicing. We include a comparison of different alignment software and an analysis of how the transcript data improved the previously published annotation. Our results demonstrate that sequencing of large numbers of full-length transcripts followed by computational mapping greatly improves identification of the complete exon structures of eukaryotic genes. In addition, we are able to find numerous introns in the untranslated regions of the genes.

MIPS Arabidopsis thaliana Database (MAtDB): an integrated biological knowledge resource based on the first complete plant genome.

Arabidopsis thaliana is the first plant for which the complete genome has been sequenced and published. Annotation of complex eukaryotic genomes requires more than the assignment of genetic elements to the sequence. Besides completing the list of genes, we need to discover their cellular roles, their regulation and their interactions in order to understand the workings of the whole plant. The MIPS Arabidopsis thaliana Database (MAtDB; http://mips.gsf.de/proj/thal/db) started out as a repository for genome sequence data in the European Scientists Sequencing Arabidopsis (ESSA) project and the Arabidopsis Genome Initiative. Our aim is to transform MAtDB into an integrated biological knowledge resource by integrating diverse data, tools, query and visualization capabilities and by creating a comprehensive resource for Arabidopsis as a reference model for other species, including crop plants.

Hurrah for Genome Projects!

Hurrah for Genome Projects!

MAGPIE/EGRET annotation of the 2.9-Mb Drosophila melanogaster Adh region.

Our challenge in annotating the 2.91-Mb Adh region of the Drosophila melanogaster genome was to identify genetic and genomic features automatically, completely, and precisely within a 6-week period. To do so, we augmented the MAGPIE microbial genome annotation system to handle eukaryotic genomic sequence data. The new configuration required the integration of eukaryotic gene-finding tools and DNA repeat tools into the automatic data collection module. It also required us to define in MAGPIE new strategies to combine data about eukaryotic exon predictions with functional data to refine the exon predictions. At the heart of the resulting new eukaryotic genome annotation system is a reverse comparison of public protein and complementary DNA sequences against the input genome to identify missing exons and to refine exon boundaries. The software modules that add eukaryotic genome annotation capability to MAGPIE are available as EGRET (Eukaryotic Genome Rapid Evaluation Tool).