Literature DB >> 21070285

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

S J Coleman1, Z Zeng, K Wang, S Luo, I Khrebtukova, M J Mienaltowski, G P Schroth, J Liu, J N MacLeod.   

Abstract

The horse, like the majority of animal species, has a limited amount of species-specific expressed sequence data available in public databases. As a result, structural models for the majority of genes defined in the equine genome are predictions based on ab initio sequence analysis or the projection of gene structures from other mammalian species. The current study used Illumina-based sequencing of messenger RNA (RNA-seq) to help refine structural annotation of equine protein-coding genes and for a preliminary assessment of gene expression patterns. Sequencing of mRNA from eight equine tissues generated 293,758105 sequence tags of 35 bases each, equalling 10.28 gbp of total sequence data. The tag alignments represent approximately 207 × coverage of the equine mRNA transcriptome and confirmed transcriptional activity for roughly 90% of the protein-coding gene structures predicted by Ensembl and NCBI. Tag coverage was sufficient to refine the structural annotation for 11,356 of these predicted genes, while also identifying an additional 456 transcripts with exon/intron features that are not listed by either Ensembl or NCBI. Genomic locus data and intervals for the protein-coding genes predicted by the Ensembl and NCBI annotation pipelines were combined with 75,116 RNA-seq-derived transcriptional units to generate a consensus equine protein-coding gene set of 20,302 defined loci. Gene ontology annotation was used to compare the functional and structural categories of genes expressed in either a tissue-restricted pattern or broadly across all tissue samples.
© 2010 The Authors, Journal compilation © 2010 Stichting International Foundation for Animal Genetics.

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Year:  2010        PMID: 21070285     DOI: 10.1111/j.1365-2052.2010.02118.x

Source DB:  PubMed          Journal:  Anim Genet        ISSN: 0268-9146            Impact factor:   3.169


  24 in total

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