The Ensembl gene annotation system

Aken, Bronwen; Ayling, Sarah; Barrell, Daniel; Clarke, Laura; Curwen, V.; Fairley, Susan; Fernandez-Banet, Julio; Billis, Konstantinos; Girón, Carlos García; Hourlier, Thibaut; Howe, Kevin; Kähäri, Andreas; Kokocinski, Felix; Martin, Fergal J.; Murphy, Daniel N.; Nag, Rishi; Ruffier, Magali; Schuster, Michael; Tang, Y. Amy; Vogel, Jan-Hinnerk; White, Simon; Zadissa, Amonida; Flicek, Paul; Searle, Stephen M. J.

doi:10.1093/database/baw093

Cited by 1,003 publications

(712 citation statements)

References 104 publications

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“…We first tested this hypothesis by counting the overlap between sweep candidate regions and protein coding genes (Ensembl release 82) (Aken et al 2016). We find no statistically significant overlap of ELS regions with protein coding genes compared to randomly placed regions of the same size (P-value = 0.671 and 0.124, for core and extended set, respectively) (Fig.…”

Section: Biological Functions Of the Candidate Regionsmentioning

confidence: 99%

Detecting ancient positive selection in humans using extended lineage sorting

et al. 2017

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Natural selection that affected modern humans early in their evolution has likely shaped some of the traits that set presentday humans apart from their closest extinct and living relatives. The ability to detect ancient natural selection in the human genome could provide insights into the molecular basis for these human-specific traits. Here, we introduce a method for detecting ancient selective sweeps by scanning for extended genomic regions where our closest extinct relatives, Neandertals and Denisovans, fall outside of the present-day human variation. Regions that are unusually long indicate the presence of lineages that reached fixation in the human population faster than expected under neutral evolution. Using simulations, we show that the method is able to detect ancient events of positive selection and that it can differentiate those from background selection. Applying our method to the 1000 Genomes data set, we find evidence for ancient selective sweeps favoring regulatory changes and present a list of genomic regions that are predicted to underlie positively selected human specific traits.[Supplemental material is available for this article.]Modern humans differ from their closest extinct relatives, Neandertals, in several aspects, including skeletal and skull morphology (Weaver 2009), and may also differ in other traits that are not preserved in the archeological record (Varki et al. 2008;Laland et al. 2010). Natural selection may have played a role in fixing these traits on the modern human lineage. However, the selection events driving the fixation would have been restricted to a specific timeframe, extending from the split between archaic and modern humans ca. 650,000 yr ago to the split of modern human populations from each other around 100,000 yr ago . While methods exist that can be used to scan the genome for the remnants of past or ongoing positive selection (Nielsen et al. 2007; Pybus and Shapiro 2009), current methods have limited power to detect positive selection on the human lineage that acted during this older timeframe (see Sabeti et al. 2006 for a review on detection methods and their timeframes): an unusually high ratio of functional changes to nonfunctional changes, such as the d N /d S test, requires millions of years and often multiple events of selection to generate detectable signals (Kryazhimskiy and Plotkin 2008), while unusual patterns of genetic diversity between individuals and populations (e.g., extended homozygosity, Tajima's D, F ST ) are most powerful during the selective sweep or shortly after (Sabeti et al. 2006;Oleksyk et al. 2010). A favorable substitution is not expected to leave a mark on linked neutral variation beyond 250,000 yr in humans (Przeworski 2002(Przeworski , 2003.The genome sequencing of archaic humans (Neandertals and Denisovans) to high coverage (Meyer et al. 2012;Prüfer et al. 2014) has spawned new methods to investigate the genetic basis of modern human traits that are not shared by the archaics (Pääbo 2014). One method, called 3P-CLR, models allele ...

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Section: Biological Functions Of the Candidate Regionsmentioning

confidence: 99%

Detecting ancient positive selection in humans using extended lineage sorting

et al. 2017

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“…Different strategies have been adopted over the past years, which essentially regroup two goals: (1) to identify transcript structure (e.g., intron vs. exon); and (2) to identify the functional potential (e.g., contains a CDS) (Pruitt et al 2009;Harrow et al 2012;Aken et al 2016;Mudge and Harrow 2016). These pipelines, however, invoke a uni-coding presumption.…”

Section: Proposition Of a Novel Annotation Frameworkmentioning

confidence: 99%

Recognition of the polycistronic nature of human genes is critical to understanding the genotype-phenotype relationship

et al. 2018

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Technological advances promise unprecedented opportunities for whole exome sequencing and proteomic analyses of populations. Currently, data from genome and exome sequencing or proteomic studies are searched against reference genome annotations. This provides the foundation for research and clinical screening for genetic causes of pathologies. However, current genome annotations substantially underestimate the proteomic information encoded within a gene. Numerous studies have now demonstrated the expression and function of alternative (mainly small, sometimes overlapping) ORFs within mature gene transcripts. This has important consequences for the correlation of phenotypes and genotypes. Most alternative ORFs are not yet annotated because of a lack of evidence, and this absence from databases precludes their detection by standard proteomic methods, such as mass spectrometry. Here, we demonstrate how current approaches tend to overlook alternative ORFs, hindering the discovery of new genetic drivers and fundamental research. We discuss available tools and techniques to improve identification of proteins from alternative ORFs and finally suggest a novel annotation system to permit a more complete representation of the transcriptomic and proteomic information contained within a gene. Given the crucial challenge of distinguishing functional ORFs from random ones, the suggested pipeline emphasizes both experimental data and conservation signatures. The addition of alternative ORFs in databases will render identification less serendipitous and advance the pace of research and genomic knowledge. This review highlights the urgent medical and research need to incorporate alternative ORFs in current genome annotations and thus permit their inclusion in hypotheses and models, which relate phenotypes and genotypes.

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“…Genome sequences and annotation GFFs were downloaded from WormBase [25] and imported into a custom Ensembl database (version 84) [26]. Using the Ensembl Perl API, the canonical transcript from each proteincoding gene was identified and exon and intron statistics were calculated.…”

Section: Gene Structure Comparisonsmentioning

confidence: 99%

Caenorhabditis monodelphis sp. n.: defining the stem morphology and genomics of the genus Caenorhabditis

et al. 2017

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Background: The genus Caenorhabditis has been central to our understanding of metazoan biology. The best-known species, Caenorhabditis elegans, is but one member of a genus with around 50 known species, and knowledge of these species will place the singular example of C. elegans in a rich phylogenetic context. How did the model come to be as it is today, and what are the dynamics of change in the genus?Results: As part of this effort to "put C. elegans in its place", we here describe the morphology and genome of Caenorhabditis monodelphis sp. n., previously known as Caenorhabditis sp. 1. Like many other Caenorhabditis, C. monodelphis sp. n. has a phoretic association with a transport host, in this case with the fungivorous beetle Cis castaneus. Using genomic data, we place C. monodelphis sp. n. as sister to all other Caenorhabditis for which genome data are available. Using this genome phylogeny, we reconstruct the stemspecies morphological pattern of Caenorhabditis. Conclusions:With the morphological and genomic description of C. monodelphis sp. n., another key species for evolutionary and developmental studies within Caenorhabditis becomes available. The most important characters are its early diverging position, unique morphology for the genus and its similarities with the hypothetical ancestor of Caenorhabditis.

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The Ensembl gene annotation system

Cited by 1,003 publications

References 104 publications

Detecting ancient positive selection in humans using extended lineage sorting

Detecting ancient positive selection in humans using extended lineage sorting

Recognition of the polycistronic nature of human genes is critical to understanding the genotype-phenotype relationship

Caenorhabditis monodelphis sp. n.: defining the stem morphology and genomics of the genus Caenorhabditis

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