MicroRNAs: small RNAs with big effects

Abstract

MicroRNAs (miRNAs) are evolutionarily conserved, small ( approximately 20-25 nucleotides), single-stranded molecules that suppress the expression of protein-coding genes by translational repression, messenger RNA degradation, or both. More than 700 miRNAs have been identified in the human genome. Amazingly, a single miRNA can regulate the expression of hundreds of mRNAs or proteins within a cell. The small RNAs are fast emerging as master regulators of innate and adaptive immunity and likely to play a pivotal role in transplantation. The clinical application of RNA sequencing ("next-generation sequencing") should facilitate transcriptome profiling at an unprecedented resolution. We provide an overview of miRNA biology and their hypothesized roles in transplantation.

Figure 1. A Schema of microRNA Participation in hematopoiesis and immune cell development and function

DC, dendritic cell; GMP, granulocyte-macrophage progenitor; MEP, megakaryocyte-erythrocyte progenitor; RBC, red blood cell; DN, double-negative T cell; DP, double positive T cell; SP, single-positive T cell; T_H-1, T helper type 1 cell; T_H-2, T helper type 2 cell; T_H-17, interleukin 17-producing helper T cell; Treg, regulatory T cell; Pro-B, pro–B cell; B-1, B-1 type B cell; B-2, B-2 type ‘conventional’ B cell; NK, natural killer; NKT, natural killer T; Pre-B, pre–B cell; pDC, plasmacytoid dendritic cell. (Figure was produced using Servier Medical Art).

Figure 2. Unsupervised hierarchical clustering and principal component analysis of miRNA expression profiles differentiate acute rejection biopsies from normal allograft biopsies of human renal allografts

(A) MicroRNA (miRNA) expression patterns of 7 human kidney allograft biopsies (3 showing histological features of acute rejection [AR] and 4 with normal allograft biopsy results [N]) were examined using microfluidic cards containing TaqMan^® probes and primer pairs for 365 human mature miRNAs. A total of 174±7 miRNAs were expressed at a significant level (i.e. C_T < 35) in all samples. The biopsies were grouped by unsupervised hierarchical clustering on the basis of similarity in expression patterns. The degree of relatedness of the expression patterns in biopsy samples is represented by the dendrogram at the top of the panel. Branch lengths represent the degree of similarity between individual samples (top) or miRNA (left). Two major clusters (top) accurately divided AR biopsies from normal allograft biopsies. Each column corresponds to the expression profile of a renal allograft biopsy, and each row corresponds to a miRNA. The color in each cell reflects the level of expression of the corresponding miRNA in the corresponding sample, relative to its mean level of expression in the entire set of biopsy samples. The increasing intensities of red mean that a specific miRNA has a higher expression in the given sample and the increasing intensities of green mean that this miRNA has a lower expression. The scale (shown at bottom right) reflects miRNA abundance ratio in a given sample relative to the mean level for all samples. (B) Principal Component Analysis of seven kidney allograft biopsies based on the expression of 174 small RNAs significantly expressed (i.e. C_T < 35) in all the samples. PCA is a bilinear decomposition method designed to reduce the dimensionality of multivariable systems and used for over viewing clusters within multivariate data. It transforms a number of correlated variables into a smaller number of uncorrelated variables called principal components (PC). The first PC accounts for as much of the variability in the data as possible, and each succeeding component accounts for as much of the remaining variability as possible. PCA showed evident clustering and confirmed the separation of AR samples from normal allograft biopsies. Samples were accurately grouped by PC1, which explained 45.91% of the overall miRNA expression variability, whereas PC2 explained 21.48% of variability and did not classified the samples according to their diagnosis (Reprinted with Permission from [20]).