ChopStitch

ChopStitch identifies putative exons and constructs splice graphs from de novo assembled transcriptomes and whole genome shotgun sequencing (WGSS) k-mer spectra to enable exon-exon boundary detection and transcript isoform discovery in non-model organisms.

Key Features:

• De Novo Exon Identification: Identifies exon-exon boundaries within de novo assembled RNA-Seq/transcriptome data.
• Bloom filter k-mer representation: Employs a Bloom filter to represent the k-mer spectrum derived from WGSS reads, enhancing exon localization.
• Handling Sequence Variability: Accounts for base substitutions arising from sequencing or assembly errors, haplotype variation, or RNA editing when defining exon candidates.
• Alternative Splicing Detection: Examines exon edges for alternative exon-exon boundaries to detect transcript isoforms.
• Output Formats: Produces putative exon sequences in FASTA format and splice graphs in DOT format.
• Implementation and Licensing: Implemented in Python and C++ and distributed under the GPL license.

Scientific Applications:

• De novo transcriptome annotation: Enables annotation of exon-intron structure in organisms lacking high-quality reference genomes.
• Alternative splicing analysis: Detects and represents transcript isoforms via splice graph construction.
• Gene structure elucidation: Supports identification of exon-exon architecture for gene model reconstruction.
• RNA editing investigation: Facilitates exploration of RNA editing events reflected as base substitutions in transcripts.
• Haplotype variation studies: Assists analysis of haplotype-specific sequence variation affecting exon boundaries.

Methodology:

Processes de novo assembled RNA-Seq/transcriptome sequences alongside WGSS reads, represents WGSS k-mer spectra with a Bloom filter, identifies exon-exon boundaries and alternative exon edges, and outputs putative exon sequences and splice graphs.