Dataset Information

XMD-miRNA-seq to generate near in vivo miRNA expression estimates in colon epithelial cells.

ABSTRACT: Accurate, RNA-seq based, microRNA (miRNA) expression estimates from primary cells have recently been described. However, this in vitro data is mainly obtained from cell culture, which is known to alter cell maturity/differentiation status, significantly changing miRNA levels. What is needed is a robust method to obtain in vivo miRNA expression values directly from cells. We introduce expression microdissection miRNA small RNA sequencing (xMD-miRNA-seq), a method to isolate cells directly from formalin fixed paraffin-embedded (FFPE) tissues. xMD-miRNA-seq is a low-cost, high-throughput, immunohistochemistry-based method to capture any cell type of interest. As a proof-of-concept, we isolated colon epithelial cells from two specimens and performed low-input small RNA-seq. We generated up to 600,000 miRNA reads from the samples. Isolated epithelial cells, had abundant epithelial-enriched miRNA expression (miR-192; miR-194; miR-200b; miR-200c; miR-215; miR-375) and overall similar miRNA expression patterns to other epithelial cell populations (colonic enteroids and flow-isolated colon epithelium). xMD-derived epithelial cells were generally not contaminated by other adjacent cells of the colon as noted by t-SNE analysis. xMD-miRNA-seq allows for simple, economical, and efficient identification of cell-specific miRNA expression estimates. Further development will enhance rapid identification of cell-specific miRNA expression estimates in health and disease for nearly any cell type using archival FFPE material.

SUBMITTER: Rosenberg AZ

PROVIDER: S-EPMC6023933 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Publications

xMD-miRNA-seq to generate near in vivo miRNA expression estimates in colon epithelial cells.

Rosenberg Avi Z AZ Wright Carrie C Fox-Talbot Karen K Rajpurohit Anandita A Williams Courtney C Porter Corey C Kovbasnjuk Olga O McCall Matthew N MN Shin Joo Heon JH Halushka Marc K MK

Scientific reports 20180628 1

Accurate, RNA-seq based, microRNA (miRNA) expression estimates from primary cells have recently been described. However, this in vitro data is mainly obtained from cell culture, which is known to alter cell maturity/differentiation status, significantly changing miRNA levels. What is needed is a robust method to obtain in vivo miRNA expression values directly from cells. We introduce expression microdissection miRNA small RNA sequencing (xMD-miRNA-seq), a method to isolate cells directly from fo ...[more]

PMID: 29955168

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Project description:High-throughput RNA-Sequencing (RNA-Seq) has become the preferred technique for studying gene expression differences between biological samples and for discovering novel isoforms, though the techniques to analyze the resulting data are still immature. One pre-processing step that is widely but heterogeneously applied is trimming, in which low quality bases, identified by the probability that they are called incorrectly, are removed. However, the impact of trimming on subsequent alignment to a genome could influence downstream analyses including gene expression estimation; we hypothesized that this might occur in an inconsistent manner across different genes, resulting in differential bias.To assess the effects of trimming on gene expression, we generated RNA-Seq data sets from four samples of larval Drosophila melanogaster sensory neurons, and used three trimming algorithms--SolexaQA, Trimmomatic, and ConDeTri-to perform quality-based trimming across a wide range of stringencies. After aligning the reads to the D. melanogaster genome with TopHat2, we used Cuffdiff2 to compare the original, untrimmed gene expression estimates to those following trimming. With the most aggressive trimming parameters, over ten percent of genes had significant changes in their estimated expression levels. This trend was seen with two additional RNA-Seq data sets and with alternative differential expression analysis pipelines. We found that the majority of the expression changes could be mitigated by imposing a minimum length filter following trimming, suggesting that the differential gene expression was primarily being driven by spurious mapping of short reads. Slight differences with the untrimmed data set remained after length filtering, which were associated with genes with low exon numbers and high GC content. Finally, an analysis of paired RNA-seq/microarray data sets suggests that no or modest trimming results in the most biologically accurate gene expression estimates.We find that aggressive quality-based trimming has a large impact on the apparent makeup of RNA-Seq-based gene expression estimates, and that short reads can have a particularly strong impact. We conclude that implementation of trimming in RNA-Seq analysis workflows warrants caution, and if used, should be used in conjunction with a minimum read length filter to minimize the introduction of unpredictable changes in expression estimates.

Dataset Information

XMD-miRNA-seq to generate near in vivo miRNA expression estimates in colon epithelial cells.

Publications

xMD-miRNA-seq to generate near in vivo miRNA expression estimates in colon epithelial cells.

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