Comparative analyses of two Geraniaceae transcriptomes using next-generation sequencing

Abstract

BackgroundOrganelle genomes of Geraniaceae exhibit several unusual evolutionary phenomena compared to other angiosperm families including accelerated nucleotide substitution rates, widespread gene loss, reduced RNA editing, and extensive genomic rearrangements. Since most organelle-encoded proteins function in multi-subunit complexes that also contain nuclear-encoded proteins, it is likely that the atypical organellar phenomena affect the evolution of nuclear genes encoding organellar proteins. To begin to unravel the complex co-evolutionary interplay between organellar and nuclear genomes in this family, we sequenced nuclear transcriptomes of two species, Geranium maderense and Pelargonium x hortorum.ResultsNormalized cDNA libraries of G. maderense and P. x hortorum were used for transcriptome sequencing. Five assemblers (MIRA, Newbler, SOAPdenovo, SOAPdenovo-trans [SOAPtrans], Trinity) and two next-generation technologies (454 and Illumina) were compared to determine the optimal transcriptome sequencing approach. Trinity provided the highest quality assembly of Illumina data with the deepest transcriptome coverage. An analysis to determine the amount of sequencing needed for de novo assembly revealed diminishing returns of coverage and quality with data sets larger than sixty million Illumina paired end reads for both species. The G. maderense and P. x hortorum transcriptomes contained fewer transcripts encoding the PLS subclass of PPR proteins relative to other angiosperms, consistent with reduced mitochondrial RNA editing activity in Geraniaceae. In addition, transcripts for all six plastid targeted sigma factors were identified in both transcriptomes, suggesting that one of the highly divergent rpoA-like ORFs in the P. x hortorum plastid genome is functional.ConclusionsThe findings support the use of the Illumina platform and assemblers optimized for transcriptome assembly, such as Trinity or SOAPtrans, to generate high-quality de novo transcriptomes with broad coverage. In addition, results indicated no major improvements in breadth of coverage with data sets larger than six billion nucleotides or when sampling RNA from four tissue types rather than from a single tissue. Finally, this work demonstrates the power of cross-compartmental genomic analyses to deepen our understanding of the correlated evolution of the nuclear, plastid, and mitochondrial genomes in plants.