Genome-wide determination of RNA stability reveals hundreds of short-lived noncoding transcripts in mammals

Abstract

Mammalian genomes produce huge numbers of noncoding RNAs (ncRNAs). However, the functions of most ncRNAs are unclear, and novel techniques that can distinguish functional ncRNAs are needed. Studies of mRNAs have revealed that the half-life of each mRNA is closely related to its physiological function, raising the possibility that the RNA stability of an ncRNA reflects its function. In this study, we first determined the half-lives of 11,052 mRNAs and 1418 ncRNAs in HeLa Tet-off (TO) cells by developing a novel genome-wide method, which we named 5'-bromo-uridine immunoprecipitation chase-deep sequencing analysis (BRIC-seq). This method involved pulse-labeling endogenous RNAs with 5'-bromo-uridine and measuring the ongoing decrease in RNA levels over time using multifaceted deep sequencing. By analyzing the relationship between RNA half-lives and functional categories, we found that RNAs with a long half-life (t(1/2) ≥ 4 h) contained a significant proportion of ncRNAs, as well as mRNAs involved in housekeeping functions, whereas RNAs with a short half-life (t(1/2) < 4 h) included known regulatory ncRNAs and regulatory mRNAs. The stabilities of a significant set of short-lived ncRNAs are regulated by external stimuli, such as retinoic acid treatment. In particular, we identified and characterized several novel long ncRNAs involved in cell proliferation from the group of short-lived ncRNAs. We designated this novel class of ncRNAs with a short half-life as Short-Lived noncoding Transcripts (SLiTs). We propose that the strategy of monitoring RNA half-life will provide a powerful tool for investigating hitherto functionally uncharacterized regulatory RNAs.

Figure 1.

5′-Bromo-uridine immunoprecipitation chase (BRIC) for measuring RNA decay in physiologically undisturbed conditions in vivo. (A) Overview of BRIC. (B) A549 cells were treated with various uridine analogs at the concentrations indicated for 48 h. The number of viable cells was counted using the Cell Counting Kit-8 (Wako). The relative abundance (100% in untreated cells) is shown in the graph. Values represent mean ± SD obtained from four replicate experiments. (C) A549 cells were treated with 5′-bromo-uridine (BrU) or Actinomycin D (ActD) at the concentrations indicated for 7 h. RNA-FISH was used to detect MALAT1 (green). Nuclear speckle proteins, SRSF2 (red) and SRRM2 (magenta), were assayed by immunostaining. Cells were counterstained with DAPI (scale bars, 10 μm). (D) Decay rates of MALAT1 were determined by BRIC and RT-qPCR (gray line) or by the Tet-off system and RT-qPCR (black line) in HeLa TO cells. Relative quantitative values at time 0 h were arbitrarily adjusted to 100%. Values represent mean ± errors obtained from duplicate experiments. The half-lives of MALAT1 using BRIC or the Tet-off system were 7.6 h and 7.0 h, respectively.

Figure 2.

Typical BRIC-seq data. (A) Typical mapping data of RNA-seq tags obtained from BRIC-seq using a Genome Analyzer (Illumina). The chromosomal locus of AK091718 is shown. (B) The relative level of AK091718 RNA remaining was determined by BRIC through deep sequencing. The numbers of sequencing tags at the various time points are shown in A. The relative quantitative values at time 0 h were arbitrarily adjusted to 100%. (C) The expression of AK091718 in HeLa TO cells assessed by Northern blot hybridization. (D) Distribution of RNA half-lives determined by BRIC-seq. BRIC-seq determined the half-lives of 11,052 mRNAs and 1418 ncRNAs expressed in HeLa TO cells. (Black circles) The fraction of mRNAs; (white circles) the fraction of ncRNAs. Transcripts with a half-life >24 h are included in the category “>24.”

Figure 3.

Representative data of mRNA stabilities. Relative levels of mRNA remaining were determined by BRIC-seq. The relative quantitative values at time 0 h were arbitrarily adjusted to 100%. (A) GO categories associated with regulatory functions. (Left) ATF1 is involved in transcription factor activity; (center) PLXNC1 is involved in multicellular organismal development; and (right) GPR157 is involved in G-protein-coupled receptor protein signaling pathway. (B) GO categories associated with housekeeping functions. (Left) SNRPB is involved with the spliceosome; (center) TIMM17B is involved with the mitochondrion; and (right) EIF3F is involved in translation.

Figure 4.

Degradation of several SLiTs was altered by all-trans retinoic acid (ATRA) in HeLa TO cells. (A) Altered abundance of SLiTs by ATRA except BC018860, whose level was below the detection limit. HeLa TO cells were untreated (gray bar) or treated with 10 mM ATRA (black bar). Values represent mean ± errors obtained from duplicate experiments. (B) Decay rates of 5 SLiTs, whose levels were increased >135% in ATRA-treated cells compared with control cells in A and of GAPDH were determined by BRIC and RT-qPCR in control cells (solid circle and black bar) and in ATRA-treated cells (open circle and gray bar). The relative quantitative values at time 0 h were arbitrarily adjusted to 100%. Values represent mean ± SD obtained from triplicate experiments [(**) P < 0.01; (*) P <0.05, Student's t-test].

Figure 5.

Functional analysis of SLiTs. (A) HeLa TO cells were treated with a control siRNA or with siRNAs targeting indicated SLiTs. The number of viable cells was counted using the Cell Counting Kit-8. Two siRNAs were used for NR_015389, AK091718, and AK055657 to rule out the possibility of an off-target effect of siRNA (black or gray bars indicate the first or second siRNA, respectively). The relative abundance (100% in control cells) is shown in the graph. Values represent mean ± SD obtained in four replicate experiments [(**) P < 0.01, Student's t-test]. (B) HeLa TO cells were treated with plasmid vectors as indicated. The number of viable cells was counted using the Cell Counting Kit-8. The relative abundance (100% with mock vector) is shown in the graph. Values represent mean ± SD in six replicate experiments [(***) P < 0.001, Student's t-test]. (C) The relative amount of RNA was quantified by RT-qPCR from nuclear fractions obtained by sucrose gradient centrifugation.