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A novel algorithm for computational identification of contaminated EST libraries.

ABSTRACT: A key goal of the Human Genome Project was to understand the complete set of human proteins, the proteome. Since the genome sequence by itself is not sufficient for predicting new genes and alternative splicing events that lead to new proteins, expressed sequence tags (ESTs) are used as the primary tool for these purposes. The high prevalence of artifacts in dbEST, however, often leads to invalid predictions. Here we describe a novel method for recognizing genomic DNA contamination and other artifacts that cannot be identified using current EST cleaning techniques. Our method uses the alignment of the entire set of ESTs to the human genome to identify highly contaminated EST libraries. We discovered 53 highly contaminated libraries and a subset of 24 766 ESTs from these libraries that probably represent contamination with genomic DNA, pre-mRNA, and ESTs that span non-canonical introns. Although this is only a small fraction of the entire EST dataset, each contaminating sequence could create a spurious transcript prediction. Indeed, in the clustering and assembly tool that we used, these sequences would have caused incorrect inference of 9575 new splice variants and 6370 new genes. Conclusions based on EST analysis, including prediction of alternative splicing, should be re-evaluated in light of these results. Our method, along with the identified set of contaminated sequences, will be essential for applications that depend on large EST datasets.

SUBMITTER: Sorek R

PROVIDER: S-EPMC149192 | biostudies-literature | 2003 Feb

REPOSITORIES: biostudies-literature

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A novel algorithm for computational identification of contaminated EST libraries.

Sorek Rotem R Safer Hershel M HM

Nucleic acids research 20030201 3

A key goal of the Human Genome Project was to understand the complete set of human proteins, the proteome. Since the genome sequence by itself is not sufficient for predicting new genes and alternative splicing events that lead to new proteins, expressed sequence tags (ESTs) are used as the primary tool for these purposes. The high prevalence of artifacts in dbEST, however, often leads to invalid predictions. Here we describe a novel method for recognizing genomic DNA contamination and other art ...[more]

PMID: 12560505

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Project description:Background:Genetic testing for BRCA1/2 germline mutations in hereditary breast/ovarian cancer patients requires screening for single nucleotide variants, small insertions/deletions and large genomic rearrangements (LGRs). These studies have long been run by Sanger sequencing and multiplex ligation-dependent probe amplification (MLPA). The recent introduction of next-generation sequencing (NGS) platforms dramatically improved the speed and the efficiency of DNA testing for nucleotide variants, while the possibility to correctly detect LGRs by this mean is still debated. The purpose of this study was to establish whether and to which extent the development of an analytical algorithm could help us translating NGS sequencing via an Ion Torrent PGM platform into a tool suitable to identify LGRs in hereditary breast-ovarian cancer patients. Methods:We first used NGS data of a group of three patients (training set), previously screened in our laboratory by conventional methods, to develop an algorithm for the calculation of the dosage quotient (DQ) to be compared with the Ion Reporter (IR) analysis. Then, we tested the optimized pipeline with a consecutive cohort of 85 uncharacterized probands (validation set) also subjected to MLPA analysis. Characterization of the breakpoints of three novel BRCA1 LGRs was obtained via long-range PCR and direct sequencing of the DNA products. Results:In our cohort, the newly defined DQ-based algorithm detected 3/3 BRCA1 LGRs, demonstrating 100% sensitivity and 100% negative predictive value (NPV) (95% CI [87.6-99.9]) compared to 2/3 cases detected by IR (66.7% sensitivity and 98.2% NPV (95% CI [85.6-99.9])). Interestingly, DQ and IR shared 12 positive results, but exons deletion calls matched only in five cases, two of which confirmed by MLPA. The breakpoints of the 3 novel BRCA1 deletions, involving exons 16-17, 21-22 and 20, have been characterized. Conclusions:Our study defined a DQ-based algorithm to identify BRCA1 LGRs using NGS data. Whether confirmed on larger data sets, this tool could guide the selection of samples to be subjected to MLPA analysis, leading to significant savings in time and money.

Project description:BACKGROUND:Ice, snow and temperatures of -14 degrees C are conditions which most animals would find difficult, if not impossible, to survive in. However this exactly describes the Arctic winter, and the Arctic springtail Onychiurus arcticus regularly survives these extreme conditions and re-emerges in the spring. It is able to do this by reducing the amount of water in its body to almost zero: a process that is called "protective dehydration". The aim of this project was to generate clones and sequence data in the form of ESTs to provide a platform for the future molecular characterisation of the processes involved in protective dehydration. RESULTS:Five normalised libraries were produced from both desiccating and rehydrating populations of O. arcticus from stages that had previously been defined as potentially informative for molecular analyses. A total of 16,379 EST clones were generated and analysed using Blast and GO annotation. 40% of the clones produced significant matches against the Swissprot and trembl databases and these were further analysed using GO annotation. Extraction and analysis of GO annotations proved an extremely effective method for identifying generic processes associated with biochemical pathways, proving more efficient than solely analysing Blast data output. A number of genes were identified, which have previously been shown to be involved in water transport and desiccation such as members of the aquaporin family. Identification of these clones in specific libraries associated with desiccation validates the computational analysis by library rather than producing a global overview of all libraries combined. CONCLUSION:This paper describes for the first time EST data from the arctic springtail (O. arcticus). This significantly enhances the number of Collembolan ESTs in the public databases, providing useful comparative data within this phylum. The use of GO annotation for analysis has facilitated the identification of a wide variety of ESTs associated with a number of different biochemical pathways involved in the dehydration and recovery process in O. arcticus.

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A novel algorithm for computational identification of contaminated EST libraries.

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A novel algorithm for computational identification of contaminated EST libraries.

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