De novo reconstruction of the Toxoplasma gondii transcriptome improves on the current genome annotation and reveals alternatively spliced transcripts and putative long non-coding RNAs

BMC Genomics

关键词: Toxoplasma;    RNA-seq;    Trinity;    LincRNA;    Alternative splicing;    Transcriptome;   

DOI  :  10.1186/1471-2164-13-696

来源: DOAJ

【 摘 要 】

Abstract

Background

Accurate gene model predictions and annotation of alternative splicing events are imperative for genomic studies in organisms that contain genes with multiple exons. Currently most gene models for the intracellular parasite, Toxoplasma gondii, are based on computer model predictions without cDNA sequence verification. Additionally, the nature and extent of alternative splicing in Toxoplasma gondii is unknown. In this study, we used de novo transcript assembly and the published type II (ME49) genomic sequence to quantify the extent of alternative splicing in Toxoplasma and to improve the current Toxoplasma gene annotations.

Results

We used high-throughput RNA-sequencing data to assemble full-length transcripts, independently of a reference genome, followed by gene annotation based on the ME49 genome. We assembled 13,533 transcripts overlapping with known ME49 genes in ToxoDB and then used this set to; a) improve the annotation in the untranslated regions of ToxoDB genes, b) identify novel exons within protein-coding ToxoDB genes, and c) report on 50 previously unidentified alternatively spliced transcripts. Additionally, we assembled a set of 2,930 transcripts not overlapping with any known ME49 genes in ToxoDB. From this set, we have identified 118 new ME49 genes, 18 novel Toxoplasma genes, and putative non-coding RNAs.

Conclusion

RNA-seq data and de novo transcript assembly provide a robust way to update incompletely annotated genomes, like the Toxoplasma genome. We have used RNA-seq to improve the annotation of several Toxoplasma genes, identify alternatively spliced genes, novel genes, novel exons, and putative non-coding RNAs.

【 授权许可】

Unknown