Using the miraEST Assembler for Reliable and Automated mRNA Transcript Assembly and SNP Detection in Sequenced ESTs (original) (raw)

1. Bastien Chevreux1,7,
2. Thomas Pfisterer2,
3. Bernd Drescher3,
4. Albert J. Driesel4,
5. Werner E.G. Müller5,
6. Thomas Wetter6, and
7. Sándor Suhai1
8. 1 Department of Molecular Biophysics, German Cancer Research Centre Heidelberg, 69120 Heidelberg, Germany
9. 2 MWG Biotech AG, 85560 Ebersberg, Germany
10. 3 RZPD German Resource Center for Genome Research, 14059 Berlin, Germany
11. 4 VitiGen AG, 76833 Siebeldingen, Germany
12. 5 Abteilung Angewandte Molekularbiologie, Institut für Physiologische Chemie, Universität Mainz, 55099 Mainz, Germany
13. 6 Institute for Medical Biometry and Informatics, University of Heidelberg, 69120 Heidelberg, Germany

Abstract

We present an EST sequence assembler that specializes in reconstruction of pristine mRNA transcripts, while at the same time detecting and classifying single nucleotide polymorphisms (SNPs) occuring in different variations thereof. The assembler uses iterative multipass strategies centered on high-confidence regions within sequences and has a fallback strategy for using low-confidence regions when needed. It features special functions to assemble high numbers of highly similar sequences without prior masking, an automatic editor that edits and analyzes alignments by inspecting the underlying traces, and detection and classification of sequence properties like SNPs with a high specificity and a sensitivity down to one mutation per sequence. In addition, it includes possibilities to use incorrectly preprocessed sequences, routines to make use of additional sequencing information such as base-error probabilities, template insert sizes, strain information, etc., and functions to detect and resolve possible misassemblies. The assembler is routinely used for such various tasks as mutation detection in different cell types, similarity analysis of transcripts between organisms, and pristine assembly of sequences from various sources for oligo design in clinical microarray experiments.

Footnotes

• ↵8 Contig as a short form of contiguous sequence, a term first coined for assembly of genomic data.

• ↵9 For example, could the base A at position 235 in read 1 be replaced by a G? (because the overall consensus at this position of the other reads suggests this possibility).

• ↵10 For example, quality clipping, sequencing vector, and cosmid vector removal can be controlled by the PREGAP4 environment provided with the GAP4 package (Bonfield et al. 1995; Bonfield and Staden 1996; Staden 1996) or the LUCY program from Chou and Holmes (2001); parts of these tasks can also be done with cross-match provided by the PHRAP package or other packages such as, for example, PFP from Paracel (Paracel 2002a).

• ↵11 Of course, a single read itself cannot be called a contig. However, putting it into the same data structure (a contig object) like the other, assembled reads is a convenient way to keep unassembled reads in the internal assembly database.

• ↵12 Based mainly on redundancy information in suspicious sequence stretches, using base-call error probabilities and signal analysis capabilities of the automatic editor very sparsely.

• Article and publication are at http://www.genome.org/cgi/doi/10.1101/gr.1917404\. Article published online before print in May 2004.

• ↵7 Corresponding author. E-MAIL bastien{at}chevreux.org; FAX +49 6227 422333.

• • Accepted January 28, 2004.
  • Received August 27, 2003.

• Cold Spring Harbor Laboratory Press

•