TransGeneScan

TransGeneScan predicts genes in assembled transcripts from metatranscriptomic sequences to enable accurate gene annotation and functional analysis of microbial communities.

Key Features:

• Strand-Specificity: Incorporates strand-specific information to predict genes on both sense and antisense transcripts.
• Short Intergenic Regions: Handles short intergenic regions typical of metatranscriptomic data to predict contiguous genes potentially within operons.
• Antisense Transcripts: Considers putative antisense transcripts to reveal regulatory interactions not captured by traditional gene finders.
• Hidden Markov Model (HMM): Employs a Hidden Markov Model that integrates strand-specificity, short intergenic regions, and antisense transcript models for gene prediction.

Scientific Applications:

• Refinement of Metagenomic Annotations: Refines annotations derived from metagenomic data by leveraging metatranscriptomic sequences to provide more detailed gene function and activity information.
• Study of Gene Regulation and Dynamics: Facilitates exploration of gene regulation mechanisms and dynamic changes in gene expression within microbial communities.
• Characterization of Functional Repertoire: Enables broad and precise profiling of gene functions to study microbial interactions, community dynamics, and environmental adaptation.

Methodology:

Uses a Hidden Markov Model integrating strand-specificity, short intergenic regions, and antisense transcript states; validated on mock metatranscriptomic datasets containing known bacterial genomes and benchmarked against MetaGeneMark, FragGeneScan, Glimmer, and GeneMark.