AnnotQTL

AnnotQTL aggregates functional annotations and maps genes within quantitative trait loci (QTL) regions to facilitate identification and characterization of candidate genes across species.

Key Features:

• Aggregation of Functional Annotations: Integrates annotations from Gene Ontology (GO), Mammalian Phenotype Ontology, Human Genome Nomenclature Committee (HGNC), and PubMed to provide comprehensive functional information for genes in QTL regions.
• Gene Localization: Maps and localizes genes to specified QTL intervals using genomic coordinates from NCBI and Ensembl.
• Synteny and Segment Conservation Analysis: Aligns human and mouse genomic segments with queried regions to support synteny and conserved segment analyses.
• Custom Marker Integration: Accepts custom marker lists and identifies genes in proximity to specified markers.
• Genome-wide Region Scanning: Identifies and retrieves all genes within regions defined by full genome scans.
• Redundancy Minimization Algorithms: Employs algorithms to minimize information redundancy while maintaining comprehensive annotation coverage.

Scientific Applications:

• Livestock Genetics: Facilitates interpretation of mapped QTLs in livestock by providing functional annotations and candidate gene lists within large QTL intervals.
• Inter-species Comparative Genomics: Supports cross-species comparisons between human and mouse to identify evolutionarily conserved QTL regions and candidate genes.
• Trait Mapping and Gene Discovery: Aids in selecting and prioritizing candidate genes for follow-up studies in trait mapping and gene discovery projects.
• Evolutionary Biology: Enables investigation of conserved genomic segments and phenotypic associations across species.

Methodology:

Aggregates functional annotations from GO, Mammalian Phenotype Ontology, HGNC, and PubMed; maps genes to QTL intervals using NCBI and Ensembl coordinates; aligns human and mouse genomic segments for synteny and segment conservation analyses; integrates custom marker lists to identify nearby genes; and applies algorithms to reduce annotation redundancy while ensuring comprehensive coverage.