Tracking and coordinating an international curation effort for the CCDS Project

Harte, Rachel A.; Farrell, Catherine; Loveland, Jane; Suner, Marie-Marthe; Wilming, Laurens G.; Aken, Bronwen; Barrell, Daniel; Frankish, Adam; Wallin, Craig; Searle, Steve; Diekhans, Mark; Harrow, Jennifer; Pruitt, Kim D.

doi:10.1093/database/bas008

Cited by 53 publications

(68 citation statements)

References 46 publications

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“…The down-sampled alignments were randomly generated from the original “full alignments” by including each read with a given probability (see Methods). As the exomes were captured using a mixture of technologies by different laboratories, we defined a common set of targets using CCDS [21]. …”

Section: Resultsmentioning

confidence: 99%

Quantifying single nucleotide variant detection sensitivity in exome sequencing

et al. 2013

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BackgroundThe targeted capture and sequencing of genomic regions has rapidly demonstrated its utility in genetic studies. Inherent in this technology is considerable heterogeneity of target coverage and this is expected to systematically impact our sensitivity to detect genuine polymorphisms. To fully interpret the polymorphisms identified in a genetic study it is often essential to both detect polymorphisms and to understand where and with what probability real polymorphisms may have been missed.ResultsUsing down-sampling of 30 deeply sequenced exomes and a set of gold-standard single nucleotide variant (SNV) genotype calls for each sample, we developed an empirical model relating the read depth at a polymorphic site to the probability of calling the correct genotype at that site. We find that measured sensitivity in SNV detection is substantially worse than that predicted from the naive expectation of sampling from a binomial. This calibrated model allows us to produce single nucleotide resolution SNV sensitivity estimates which can be merged to give summary sensitivity measures for any arbitrary partition of the target sequences (nucleotide, exon, gene, pathway, exome). These metrics are directly comparable between platforms and can be combined between samples to give “power estimates” for an entire study. We estimate a local read depth of 13X is required to detect the alleles and genotype of a heterozygous SNV 95% of the time, but only 3X for a homozygous SNV. At a mean on-target read depth of 20X, commonly used for rare disease exome sequencing studies, we predict 5–15% of heterozygous and 1–4% of homozygous SNVs in the targeted regions will be missed.ConclusionsNon-reference alleles in the heterozygote state have a high chance of being missed when commonly applied read coverage thresholds are used despite the widely held assumption that there is good polymorphism detection at these coverage levels. Such alleles are likely to be of functional importance in population based studies of rare diseases, somatic mutations in cancer and explaining the “missing heritability” of quantitative traits.

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Section: Resultsmentioning

confidence: 99%

Quantifying single nucleotide variant detection sensitivity in exome sequencing

et al. 2013

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“…We mapped at least two peptides to 63.9% of the human gene set and identified alternative splice isoforms for just 246 human genes; this clearly suggests that the vast majority of genes express a single main protein isoform. These main experimental isoforms found strong support from both consensus coding sequence (CCDS) transcripts 16 and APPRIS principal isoforms, 17 whereas the agreement with dominant transcripts from RNAseq data was less clear.…”

Section: Introductionmentioning

confidence: 95%

Most Highly Expressed Protein-Coding Genes Have a Single Dominant Isoform

et al. 2015

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Although eukaryotic cells express a wide range of alternatively spliced transcripts, it is not clear whether genes tend to express a range of transcripts simultaneously across cells, or produce dominant isoforms in a manner that is either tissue-specific or regardless of tissue. To date, large-scale investigations into the pattern of transcript expression across distinct tissues have produced contradictory results. Here, we attempt to determine whether genes express a dominant splice variant at the protein level. We interrogate peptides from eight large-scale human proteomics experiments and databases and find that there is a single dominant protein isoform, irrespective of tissue or cell type, for the vast majority of the protein-coding genes in these experiments, in partial agreement with the conclusions from the most recent large-scale RNAseq study. Remarkably, the dominant isoforms from the experimental proteomics analyses coincided overwhelmingly with the reference isoforms selected by two completely orthogonal sources, the consensus coding sequence variants, which are agreed upon by separate manual genome curation teams, and the principal isoforms from the APPRIS database, predicted automatically from the conservation of protein sequence, structure, and function.

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“…This set also includes all current human Consensus Coding Sequence (CCDS) gene models (16). Manual annotation from Havana is also incorporated into our gene sets on alternate releases for mouse and zebrafish.…”

Section: Introductionmentioning

confidence: 99%

Ensembl 2013

Flicek

Ahmed

Amode

et al. 2012

Nucleic Acids Research

896

942

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The Ensembl project (http://www.ensembl.org) provides genome information for sequenced chordate genomes with a particular focus on human, mouse, zebrafish and rat. Our resources include evidenced-based gene sets for all supported species; large-scale whole genome multiple species alignments across vertebrates and clade-specific alignments for eutherian mammals, primates, birds and fish; variation data resources for 17 species and regulation annotations based on ENCODE and other data sets. Ensembl data are accessible through the genome browser at http://www.ensembl.org and through other tools and programmatic interfaces.

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Tracking and coordinating an international curation effort for the CCDS Project

Cited by 53 publications

References 46 publications

Quantifying single nucleotide variant detection sensitivity in exome sequencing

Quantifying single nucleotide variant detection sensitivity in exome sequencing

Most Highly Expressed Protein-Coding Genes Have a Single Dominant Isoform

Ensembl 2013

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