Differential sensitivity of target genes to translational repression by miR-17~92

MicroRNAs (miRNAs) are thought to exert their functions by modulating the expression of hundreds of target genes and each to a small degree, but it remains unclear how small changes in hundreds of target genes are translated into the specific function of a miRNA. Here, we conducted an integrated analysis of transcriptome and translatome of primary B cells from mutant mice expressing miR-17~92 at three different levels to address this issue. We found that target genes exhibit differential sensitivity to miRNA suppression and that only a small fraction of target genes are actually suppressed by a given concentration of miRNA under physiological conditions. Transgenic expression and deletion of the same miRNA gene regulate largely distinct sets of target genes. miR-17~92 controls target gene expression mainly through translational repression and 5’UTR plays an important role in regulating target gene sensitivity to miRNA suppression. These findings provide molecular insights into a model in which miRNAs exert their specific functions through a small number of key target genesCX is a Pew Scholar in Biomedical Sciences. This study is supported by the PEW Charitable Trusts, Cancer Research Institute, National Institute of Health (R01AI087634, R01AI089854, RC1CA146299, R56AI110403, and R01AI121155 to CX), National Natural Science Foundation of China (31570882 to WHL, 31570883 to NX, 31570911 to GF, 91429301 to JH, 31671428 and 31500665 to YZ), 1000 Young Talents Program of China (K08008 to NX), 100 Talents Program of The Chinese Academy of Sciences (YZ), National Program on Key Basic Research Project of China (2016YFA0501900 to YZ), the Fundamental Research Funds for the Central Universities of China (20720150065 to NX and GF), Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2015R1C1A1A01052387 to SGK, NRF-2016R1A4A1010115 to SGK and PHK), and 2016 Research Grant from Kangwon National University (SGK)

Comparative UAV and field phenotyping to assess yield and nitrogen use efficiency in hibrid and conventional barley

With the commercialization and increasing availability of Unmanned Aerial Vehicles (UAVs) multiple rotor copters have expanded rapidly in plant phenotyping studies with their ability to provide clear, high resolution images. As such, the traditional bottleneck of plant phenotyping has shifted from data collection to data processing. Fortunately, the necessarily controlled and repetitive design of plant phenotyping allows for the development of semi-automatic computer processing tools that may sufficiently reduce the time spent in data extraction. Here we present a comparison of UAV and field based high throughput plant phenotyping (HTPP) using the free, open-source image analysis software FIJI (Fiji is just ImageJ) using RGB (conventional digital cameras), multispectral and thermal aerial imagery in combination with a matching suite of ground sensors in a study of two hybrids and one conventional barely variety with ten different nitrogen treatments, combining different fertilization levels and application schedules. A detailed correlation network for physiological traits and exploration of the data comparing between treatments and varieties provided insights into crop performance under different management scenarios. Multivariate regression models explained 77.8, 71.6, and 82.7% of the variance in yield from aerial, ground, and combined data sets, respectively

Ribosome accumulation in 5’UTR correlates with translational repression of target genes.

<p>(<b>A-C</b>) Ribosome accumulation in 5’UTRs of ribo-upregulated TKO targets in WT B cells (<b>A</b>), ribo-downregulated TG targets in TG B cells (<b>B</b>), but not in 5’UTRs of other targets (<b>C</b>). Ribosome occupancy in 5’UTR was normalized to the overall ribosome footprint abundance of the same gene [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006623#pgen.1006623.ref096" target="_blank">96</a>]. The first nucleotide of start codon is set as position 0 (grey dashed line). (<b>D</b>) Inverse correlation between ribosome occupancy in 5’UTR and the overall ribosome density on target mRNA in WT B cells. (<b>E</b>) High GC content in 5’UTRs of ribo-upregulated TKO targets.</p

Quantification of miR-17~92 miRNAs and binding sites in primary B cells.

<p>(<b>A,B</b>) Quantitative Northern blot to determine miR-17~92 miRNA copy numbers. Indicated amounts of synthetic miR-17, miR-18a, miR-19b and miR-92 were added to naïve and activated TKO B cells before RNA extraction. The copy numbers of each miRNA subfamily were determined by Northern blot comparing WT B cells and TKO B cells with graded amounts of spike-in synthetic miRNAs, using a mixture of probes corresponding to all members of a miRNA subfamily (also see <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006623#pgen.1006623.s029" target="_blank">S7 Table</a></b>). Naïve B cells were activated with LPS and IL-4 for indicated amounts of time (h, hour). (<b>C-E</b>) Summary of miR-17~92 family miRNA copy numbers (<b>C</b>), conserved miR-17~92 family miRNA binding sites (<b>D</b>) (also see <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006623#pgen.1006623.s030" target="_blank">S8 Table</a></b>), and ratios of conserved miR-17~92 family miRNA binding sites to miRNAs (<b>E</b>) in naïve and activated B cells.</p

Target genes exhibit different sensitivity to miR-17~92 expression level changes.

<p><b>(A)</b> Minimal overlap between ribo-upregulated TKO targets and ribo-downregulated TG targets. <b>(B-D)</b> The responses of ribosome density of ribo-upregulated TKO targets <b>(B)</b> and ribo-downregulated TG targets <b>(C)</b> to three miR-17~92 expression levels. Translated genes lacking miR-17~92 binding sites were used as control <b>(D)</b>. Colored bars indicate median values and error bars represent interquartile ranges. Each dot represents relative ribosome density of a unique gene. Numbers indicate p-values. <b>(E)</b> Different sensitivity of individual target genes to miR-17~92 expression level changes. Protein levels were determined by immunoblot and normalized to β-Actin (<b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006623#pgen.1006623.s007" target="_blank">S7</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006623#pgen.1006623.s011" target="_blank">S11</a> Figs</b>). Target gene protein levels in WT B cells were arbitrarily set as 1.0 (n≥4). Vertical lines indicate error bars. <b>(F)</b> Relative mRNA levels of individual target genes in TKO, WT and TG B cells as determined by microarray (n = 3). <b>(G)</b> A hypothetical curve depicting target gene protein level change as a function of miRNA concentration. For a miRNA-target mRNA interaction in a given cellular context, there are a threshold level and a saturation level of miRNA concentration. miRNA suppresses target gene expression in a dose-dependent manner when miRNA concentration is between the threshold and saturation levels. Suppression does not occur when miRNA concentration is below the threshold level, while suppression reaches a maximal when miRNA concentration is above the saturation level. <b>(H)</b> The hypothetical response curves of group1, group2 and group3 target genes to miR-17~92 expression level changes. Note that the difference in amplitude for individual target genes is not depicted in this graph.</p

Regulation of target gene sensitivity to miRNA suppression by 5’UTR.

<p>(<b>A</b>) An engineered psiCheck2 vector (psiCheck-2-pd) for investigating the effect of 5’UTR and 3’UTR on reporter gene expression. TSS, transcription start site. (<b>B</b>) Experimental scheme of reporter assays in primary B cells. FACS plots show electroporation efficiency using a GFP-expressing plasmid. (<b>C,D</b>) Dual luciferase reporter assay to determine the effect of 5’UTR and 3’UTR on the reporter gene protein (luciferase activity) (<b>C</b>) and mRNA (qRT-PCR) levels (<b>D</b>). Closed and open circles indicate reporters with wild-type (wt) and mutated (mut) <i>CD69</i> 3’UTR, respectively. A comparison of renilla luciferase activity normalized to firefly luciferase activity (hRluc/Fluc) between psiCheck-2-pd containing mut and wt <i>CD69</i> 3’UTR reveals the sensitivity of the renilla luciferase mRNA (hRluc) to miR-17~92-mediated suppression. Results of normalized hRlcu/Fluc (n = 10) are from three independent experiments. Each experiment contained 3–4 replicates.</p