Using Deep RNA Sequencing for the Structural Annotation of the Laccaria Bicolor Mycorrhizal Transcriptome

Abstract

BackgroundAccurate structural annotation is important for prediction of function and required for in vitro approaches to characterize or validate the gene expression products. Despite significant efforts in the field, determination of the gene structure from genomic data alone is a challenging and inaccurate process. The ease of acquisition of transcriptomic sequence provides a direct route to identify expressed sequences and determine the correct gene structure.MethodologyWe developed methods to utilize RNA-seq data to correct errors in the structural annotation and extend the boundaries of current gene models using assembly approaches. The methods were validated with a transcriptomic data set derived from the fungus Laccaria bicolor, which develops a mycorrhizal symbiotic association with the roots of many tree species. Our analysis focused on the subset of 1501 gene models that are differentially expressed in the free living vs. mycorrhizal transcriptome and are expected to be important elements related to carbon metabolism, membrane permeability and transport, and intracellular signaling. Of the set of 1501 gene models, 1439 (96%) successfully generated modified gene models in which all error flags were successfully resolved and the sequences aligned to the genomic sequence. The remaining 4% (62 gene models) either had deviations from transcriptomic data that could not be spanned or generated sequence that did not align to genomic sequence. The outcome of this process is a set of high confidence gene models that can be reliably used for experimental characterization of protein function.Conclusions69% of expressed mycorrhizal JGI “best” gene models deviated from the transcript sequence derived by this method. The transcriptomic sequence enabled correction of a majority of the structural inconsistencies and resulted in a set of validated models for 96% of the mycorrhizal genes. The method described here can be applied to improve gene structural annotation in other species, provided that there is a sequenced genome and a set of gene models.

Biosynthesis of Terpenoid Natural Products in Fungi

“…Deep RNA sequencing has been shown to significantly improve the accuracy of a large fraction of the gene models for Laccaria bicolor by finding all splice sites in genes through deep sequence coverage; one single transcriptome data set of 30 million reads provided 30 times more sequence coverage and hence much greater resolution for gene structure annotation than the EST libraries available for this fungus [240]. So far, only some of the more recently sequenced genomes have associated deep RNA sequence data [228,230].…”

Transcriptome and Proteome Exploration to Provide a Resource for the Study of Agrocybe aegerita

“…Transcriptome provides information on transcript quantity and gene expression variation. To date, the high-throughput sequencing has been applied to the genome/transcriptome analysis of higher fungi, including Coprinopsis cinerea [22], Laccaria bicolor [23], [24], Schizophyllum commune [25] and Ganoderma lucidum [26]. High-throughput sequencing technology (next-generation sequencing technology) has already revolutionized the way we study the transcriptome.…”

Genome-Wide Transcriptome and Proteome Analysis on Different Developmental Stages of Cordyceps militaris

“…With the development of sequencing technique and mycology, the genomes or transcriptomes of fungi have been increasingly obtained for further research, including Metarhizium species [36], Coprinus cinerea [37], Trichoderma reesei [38], Schizophyllum commune [39], Laccaria bicolor [40], [41], Tuber melanosporum [42], [43], Postis placenta [44], [45]. By mapping the sequenced transcriptome reads to a reference genome, the structure annotation can be improved and novel transcripts and alternative splicing can be predicted, which expand the current genome databases [31], [42], [46].…”