Structural annotation of equine protein-coding genes determined by mRNA sequencing.

Area of Science:

• Genomics
• Transcriptomics
• Bioinformatics

Background:

• Limited species-specific expressed sequence data hinders accurate equine gene annotation.
• Existing equine gene models often rely on predictions and cross-species comparisons.
• Accurate gene models are crucial for understanding equine biology and health.

Purpose of the Study:

• To refine structural annotation of equine protein-coding genes using RNA-sequencing (RNA-seq).
• To conduct a preliminary assessment of gene expression patterns across eight equine tissues.
• To generate a consensus equine protein-coding gene set.

Main Methods:

• Illumina-based RNA-seq was performed on eight equine tissues.
• Generated over 293 million sequence tags (10.28 gbp) for transcriptome analysis.
• Combined RNA-seq data with existing Ensembl and NCBI annotations to create a consensus gene set.

Main Results:

• RNA-seq confirmed transcriptional activity for ~90% of predicted equine genes.
• Refined structural annotation for 11,356 genes and identified 456 novel transcripts.
• Established a consensus equine protein-coding gene set of 20,302 loci.

Conclusions:

• RNA-seq significantly improves the accuracy and completeness of equine gene annotation.
• The generated consensus gene set provides a valuable resource for equine genomics research.
• Tissue-specific and broad gene expression patterns were preliminarily assessed.