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Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data

ABSTRACT: Small RNA sequencing can be used to gain an unprecedented amount of detail into the microRNA transcriptome. The relatively high cost and low throughput of sequencing bases technologies can potentially be offset by the use of multiplexing. However multiplexing involves a tradeoff between increased number of sequenced samples and reduced number of reads per sample (i.e. lower coverage). To assess the effect of different depths of coverage due to multiplexing on microRNA differential expression and detection, we sequenced the small RNA of lung tissue samples collected in a clinical setting by multiplexing 1, 3, 6, 9, or 12 samples per lane using the Illumina HiSeq 2000. As expected, the numbers of reads obtained per sample decreased as the number of samples in a multiplex increased. Furthermore, after normalization replicate samples included in distinct multiplexes were highly correlated (R > 0.97). When detecting differential microRNA expression between groups of samples, microRNAs with average expression greater than 1 reads per million (RPM) had reproducible fold change estimates (signal to noise) independent of the degree of multiplexing. The number of microRNAs detected was strongly correlated with the Log2 number of reads aligning to microRNA loci (R=0.96). However, most additional microRNAs detected in samples with greater sequencing coverage were in the range of expression which had lower fold change reproducibility. These findings elucidate the tradeoff between increasing the number of samples in a multiplex with decreasing coverage and will aid in the design of large-scale clinical studies exploring microRNA expression and its role in disease.

ORGANISM(S): Homo sapiens

PROVIDER: GSE56861 | GEO | 2014/12/29

SECONDARY ACCESSION(S): PRJNA244782

REPOSITORIES: GEO

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Project description:ChIP-seq experiments are standard experimental procedure for interrogating epigenetic states and protein-DNA interactions. Sequencing experiments are often designed according to the trade-off between the need to obtain maximum sequencing coverage limited funds. Multiplexing samples is a common approach to minimize cost and maximize information yield. We therefore performed an extensive ChiP-seq multiplexing study to gain a better understanding of the effect of multiplexing on the resulting peak detection and genomic annotation and to provide solid guidelines for multiplexing ChIP-seq studies. For a well characterized antibody, our results indicate that multiplexing to ~20M reads (roughly 8 samples per sequencing lane) is sufficient to capture most of the biological signal. Multiplexing samples in sequencing experiments is a common approach to maximize information yield while minimizing cost. In most cases the number of samples that are multiplexed is determined by financial consideration or experimental convenience with limited understanding on the effects on the experimental results. Here we set to examine the impact of multiplexing ChIP-seq experiments on the ability to identify a specific epigenetic modification. We performed an analysis of peak detection to determine the effects of multiplexing. These include false discovery rates, size, position and statistical significance of peak detection and changes in gene annotation. We found that, for histone marker H3K4me3, one can multiplex up to 8 samples (7 IP + 1 input) at ~21 million reads each and still detect over 90% of all peaks found when using a full lane for sample. Furthermore, there are no variations introduced by indexing or lane batch effects and importantly there is no significant reduction in the number of genes with neighboring H3K4me3 peaks. We conclude that, for a well characterized antibody and therefore, model IP condition, multiplexing 8 samples per lane is sufficient to capture most of the biological signal.

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Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data

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