BackgroundRNA sequencing (RNA-Seq) has emerged as a powerful approach for the detection of differential gene expression with both high-throughput and high resolution capabilities possible depending upon the experimental design chosen. Multiplex experimental designs are now readily available, these can be utilised to increase the numbers of samples or replicates profiled at the cost of decreased sequencing depth generated per sample. These strategies impact on the power of the approach to accurately identify differential expression. This study presents a detailed analysis of the power to detect differential expression in a range of scenarios including simulated null and differential expression distributions with varying numbers of biological or technical replicates, sequencing depths and analysis methods.ResultsDifferential and non-differential expression datasets were simulated using a combination of negative binomial and exponential distributions derived from real RNA-Seq data. These datasets were used to evaluate the performance of three commonly used differential expression analysis algorithms and to quantify the changes in power with respect to true and false positive rates when simulating variations in sequencing depth, biological replication and multiplex experimental design choices.ConclusionsThis work quantitatively explores comparisons between contemporary analysis tools and experimental design choices for the detection of differential expression using RNA-Seq. We found that the DESeq algorithm performs more conservatively than edgeR and NBPSeq. With regard to testing of various experimental designs, this work strongly suggests that greater power is gained through the use of biological replicates relative to library (technical) replicates and sequencing depth. Strikingly, sequencing depth could be reduced as low as 15% without substantial impacts on false positive or true positive rates.

BackgroundWheat stem rust, caused by Puccinia graminis f. sp. tritici, is a major wheat disease which is mainly controlled through the release of resistant cultivars containing one or several resistance genes. Considerable effort has been put into the discovery of new resistance genes, but knowledge of their mechanisms of action is often lacking. In this study, the mechanism of resistance conferred by a recently discovered stem rust resistance locus on wheat chromosome 7AL was investigated through microscopic observations and RNA-sequencing, using the susceptible line Columbus and the independent, backcrossed, resistant lines Columbus-NS765 and Columbus-NS766.ResultsMicroscopic observations of infected leaves revealed that the resistance conferred by the 7AL resistance locus was initiated 2 days post-inoculation, upon the fungus entry into the plant through the stoma. Resistance was manifested by death of guard and epidermal cells adjacent to an infection site. Occasionally, similar observations were made in the susceptible line, suggesting that the resistance response was the same in all genotypes, but enhanced in the resistant lines. Transcriptomic analysis, combined with assignment of genes to wheat chromosomes, revealed a disproportionately high number of differentially expressed genes were located on chromosomes 7AL and 6A. A number of genes annotated as cysteine-rich receptor-like kinases were located on chromosome 7AL. Closer investigation indicated that the encoded proteins were in fact putative receptor-like cytoplasmic kinases. One of the putative RLCK genes contained a SNP marker previously shown to co-segregate with the 7AL resistance locus. The results also indicated the presence of a large introgression on chromosome 6A in both resistant lines, but whether it has any role in the resistance response is unclear.ConclusionsThis study represents the first investigation on the resistance mechanism conferred by the wheat 7AL stem rust resistance locus. The resistance response was associated with pre-haustorial cell death, and the transcriptome analysis suggested putative receptor-like cytoplasmic kinases as candidate resistance genes for further investigation.Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-016-2320-z) contains supplementary material, which is available to authorized users.