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. 2010 Nov;20(11):1590-604.
doi: 10.1101/gr.107995.110. Epub 2010 Oct 8.

Next-generation sequencing identifies the natural killer cell microRNA transcriptome

Todd A Fehniger  1 , Todd Wylie, Elizabeth Germino, Jeffrey W Leong, Vincent J Magrini, Sunita Koul, Catherine R Keppel, Stephanie E Schneider, Daniel C Koboldt, Ryan P Sullivan, Michael E Heinz, Seth D Crosby, Rakesh Nagarajan, Giridharan Ramsingh, Daniel C Link, Timothy J Ley, Elaine R Mardis
Affiliations

Next-generation sequencing identifies the natural killer cell microRNA transcriptome

Todd A Fehniger et al. Genome Res. 2010 Nov.

Abstract

Natural killer (NK) cells are innate lymphocytes important for early host defense against infectious pathogens and surveillance against malignant transformation. Resting murine NK cells regulate the translation of effector molecule mRNAs (e.g., granzyme B, GzmB) through unclear molecular mechanisms. MicroRNAs (miRNAs) are small noncoding RNAs that post-transcriptionally regulate the translation of their mRNA targets, and are therefore candidates for mediating this control process. While the expression and importance of miRNAs in T and B lymphocytes have been established, little is known about miRNAs in NK cells. Here, we used two next-generation sequencing (NGS) platforms to define the miRNA transcriptomes of resting and cytokine-activated primary murine NK cells, with confirmation by quantitative real-time PCR (qRT-PCR) and microarrays. We delineate a bioinformatics analysis pipeline that identified 302 known and 21 novel mature miRNAs from sequences obtained from NK cell small RNA libraries. These miRNAs are expressed over a broad range and exhibit isomiR complexity, and a subset is differentially expressed following cytokine activation. Using these miRNA NGS data, miR-223 was identified as a mature miRNA present in resting NK cells with decreased expression following cytokine activation. Furthermore, we demonstrate that miR-223 specifically targets the 3' untranslated region of murine GzmB in vitro, indicating that this miRNA may contribute to control of GzmB translation in resting NK cells. Thus, the sequenced NK cell miRNA transcriptome provides a valuable framework for further elucidation of miRNA expression and function in NK cell biology.

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Figures

Figure 1.
Figure 1.
Known miRNAs sequenced in resting and activated NK cells using the Illumina GA. (A) Distribution of miRNA sequences in resting and activated NK cells based on the total read counts. Mature miRNA sequences are categorized by the number of read counts corresponding to each individual miRNA. (B) Top 20 known miRNAs expressed in resting and activated NK cells. The percent contribution of each miRNA sequence to the total pool of known miRNA sequences was calculated by dividing individual miRNA read counts by the total number of known miRNA sequence reads in that cDNA library. (C) Top 10 known miRNAs constitute ∼65% of total miRNA reads in NK cells.
Figure 2.
Figure 2.
Mature miRNA sequence variation (isomiRs) detected by Illumina GA sequencing of NK cell miRNAs. (A) Example miR-21 isomiRs illustrate the complexity of miRNA sequences identified by Illumina sequencing. Shown are selected isomiR sequences that match or do not match the reference genome and their percent contribution to miR-21 read counts (mature miR-21 sequence annotated in bold). We further divide those reads not matching the reference genome into sequences that may arise by a known RNA editing event and all others. A complete breakdown of isomiR sequence variation for all miRNAs is provided in the Supplemental material. (B) Distribution of miRNA mature sequences by the number of isomiRs identified by Illumina GA sequencing. (C) Comparison of isomiR sequences between resting and activated NK cell libraries. Scatterplot showing the percent contribution of a given isomiR in each library, with each dot representing one isomiR. Analysis was limited to the top five isomiRs and the top 125 miRNAs by expression. In general, isomiRs were found in very similar distributions in resting and activated NK cells (r2 = 0.91).
Figure 3.
Figure 3.
Novel miRNA genes identified in NK cells. (A) Predicted secondary fold structure of a novel miRNA precursor hairpin cluster-936 (mmu-mir-1306) (16:18284332..18284410) identified in Illumina GA–sequenced NK cell small RNAs (predicted ΔG = −30.7). Mature miRNA is noted in blue, minor star species in green. (B) Read alignment coverage map (RefCov) of novel miRNA gene demonstrating the specific alignment of sequences to the mature miRNA sequence. Shown is the nucleotide position of the precursor (x-axis) and the number of reads aligning to each nucleotide position (y-axis). Coverage models for total (sum = resting and activated), resting, and activated NK libraries are shown. (C) IsomiR analysis of novel miRNA with mature sequence noted in blue, and the read counts and corresponding percentage contribution to the total number of reads aligning to this novel hairpin.
Figure 4.
Figure 4.
Comparison of miRNA detection by Illumina GA and ABI SOLiD sequencing and hybridization-based techniques. Known miRNAs were identified in cDNA libraries created from small RNAs from resting or activated primary mouse NK cells by SHRiMP alignment to miRBase v13 hairpin precursor-miRNAs. For each miRNA detected on either platform, the dot shows the relative expression by normalized read count from Illumina (x-axis) and SOLiD (y-axis) in the resting NK cell (A) or activated NK cell (B) libraries. Overall, the correlation for detection was high (0.75). The top 20 miRNAs detected in both NK cell libraries for Illumina (C) and SOLiD (D) are shown rank ordered based on platform. (E) Venn diagram of overlapping detection in resting and activated NK cell libraries comparing Illumina and SOLiD sequencing. For miRNA detected in only one platform-data set, the normalized read count distribution is shown, highlighting that most discrepant miRNAs are expressed at relatively low levels. (F) Venn diagram showing the breakdown of overlap between Illumina GA sequencing, SOLiD sequencing, AB real-time qRT-PCR, and Agilent microarrays for 136 miRNAs with probes available for both qRT-PCR and microarrays. Detection by qRT-PCR was defined as a ΔCt (compared to MammU6) of <15, and for microarrays a normalized signal intensity of >1.0. Rare cases of major differences in the normalized read counts were detected by Illumina GA and SOLiD (Supplemental Table S4).
Figure 5.
Figure 5.
miR-223 is down-regulated with IL15 activation and directly targets the murine GzmB 3′ UTR. (A) Mature miR-223 decreases in abundance in resting NK cells following 24 h of IL15 activation on multiple platforms, including Illumina, SOLiD, microarray, and qRT-PCR. (B) Time course of mature miR-223 down-regulation in mouse NK cells at indicated time points after rmIL15 activation assayed by ABI qRT-PCR assay (N = 3–7 independent experiments). (C) Schema of miR-223 binding site in murine GzmB 3′-UTR sequencing (seed sequence highlighted with bold/underline). Mutated GzmB Δ3′ UTR eliminates the seed binding sites (italics). (D) miR-223 selectively targets the GzmB 3′ UTR. psiCheck2 sensor plasmids containing the GzmB 3′ UTR, Prf1 3′ UTR (negative control), or no 3′ UTR (negative control) were cotransfected in 293T cells with an MND-GFP-miRNA overexpression vector containing a mini-gene of mir-223, mir-21 (negative control), or no miRNA (negative control). Overexpression of miR-223 selectively decreased the luciferase expression compared to no miRNA or miRNA-21 controls. No down-regulation of luciferase was observed for negative control (Prf1 3′ UTR or no 3′ UTR) with miR-223 overexpression. (E) miR-223 targeting of GzmB 3′ UTR is direct. miR-223 down-regulates luciferase controlled by the endogenous GzmB 3′ UTR, but fails to down-regulate luciferase controlled by the GzmB Δ3′ UTR (see B), which lacks the predicted miR-223 seed sequence.
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