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Several recent studies have shown that lncRNAs play an essential role in almost every important biological process and that this role is achieved through the control of gene expression occurring both at the transcriptional and the post-transcriptional levels showing in this latter case that RNAs may be the target of lncRNAs6.
The lncRNA Nuclear enriched abundant transcript 1 (Neat1) is implicated in different neuropathologies as frontotemporal dementia, amyotrophic lateral sclerosis, or epilepsy8,9,10, and is also misregulated in different cancers11,12.
This lncRNA is also known to be the structural component of specific nuclear bodies, the paraspeckles, and to be involved in post-transcriptional circadian regulation of gene expression13. Paraspeckles that are found in every cell nucleus and are formed around not only Neat1, which is necessary for their formation, but also around several RNA binding proteins (RBP)14, are indeed known to be able to retain RNA targets within the nucleus15. The formation of paraspeckles is achieved through the association of the different components. This formation was shown to display a circadian rhythmic pattern driving a rhythmic nuclear retention of RNA targets13. The nuclear retention of RNA targets by paraspeckles may occur through binding to RBP or directly through RNA/RNA association, but the extent of RNAs targeted by paraspeckles had to be determined. To identify the RNA targeted directly or indirectly by Neat1, an RNA pull-down protocol was designed that allows the isolation and the identification of all Neat1 RNA targets in cultured cells as well as in tissue samples (see Figure 1 for a graphical presentation of the technique).
The protocol was also successfully applied to the identification of RNA targets of an another lncRNA Metastasis Associated Lung Adenocarcinoma Transcript 1 (Malat1). Malat1 is a highly conserved and expressed lncRNA found in nuclear speckles together with several RNA splicing factors. Malat1 is known to be involved in the regulation of the splicing of several nascent pre-mRNA16,17.
Specific (SO) and non-specific oligonucleotide (NSO) probes were generated using the probe design strategy described here. This strategy relies on the selection of regions that display a low probability of internal base pairing as predicted by the secondary structure of the lncRNA and on the design of specific probes with a strong affinity for these regions. As a representative result of these bioinformatics predictions, a picture of the predicted secondary structure of a sequence of Neat1 (nucleotides 1,480 to 2,000) together with the position of two designed SO probes are given in Figure 2.
The designed probes were directed to rat Neat1 or Malat1 for GH4C1 cultured cells and to mouse Neat1 for pituitary tissue extracts (Table 1). The relative enrichment in Neat1 or Malat1 was calculated for non-specific and specific probes relative to the input samples. Figure 3 shows the efficiency of the specific probes to pull-down Neat1 in the rat GH4C1 pituitary cell line (Figure 3A) and in mouse pituitary tissue extracts (Figure 3B). When using the probe design protocol to generate specific oligonucleotide (SO) probes directed to Malat1, one efficient probe was obtained while another was not efficient enough and was discarded (Figure 4A).
After an RNA pull-down procedure followed by RT-qPCR experiments, some RNAs assessed with specific primers (Table 1) were shown to be associated with Neat1 or Malat1 in GH4C1 extracts. The RNAs associated with Neat1 in GH4C1 cell extracts were also shown to be associated with Neat1 in pituitary tissue extracts. Indeed, after Neat1 RNA pull-down, Malat1 was found to be targeted by Neat1 both in the GH4C1 cell line and in pituitary mouse tissue extracts (Figure 5A). Reciprocally, Neat1 was significantly enriched after Malat1 RNA pull-down performed with a specific probe in GH4C1 cells (Figure 4B). By highlighting the close relationship between the two lncRNAs, these results are consistent with the potential co-regulatory role of Neat1 and Malat1 suggested by Malat1 knockout mice that display variations in Neat1 RNA expression18,19. The transcripts of two main pituitary hormones, growth hormone (Gh) (Figure 5B) and prolactin (Prl) (Figure 5C) were significantly enriched following Neat1 RNA pull-down with specific probes in both GH4C1 cells and pituitary extracts, suggesting a possible regulation of the two hormones by Neat1. When comparing the two specific probes used, it appeared that their efficiency could vary depending on the RNA target considered (Figure 5B and Figure 5C). These results highlight the necessity of designing several specific probes in order to select those displaying not only the best efficiency in the enrichment of the pull-down lncRNA, but also the best efficiency in the enrichment of its RNA targets.
The RNA pull-down method can also be followed by RNA high-throughput sequencing to obtain the comprehensive list of RNA targets of a lncRNA of interest13. An RNA-seq analysis on GH4C1 pituitary cells after Neat1 RNA pull-down using the two specific probes described above was performed. It should be noted that a negative control using a NSO could also be subjected to RNA-seq analysis, if the level of RNA recovered after the RNA pull-down with NSO is sufficient to allow the construction of libraries. This was not the case in previous experience13. Libraries that were generated after use of specific probes were analyzed using Tophat/cufflinks pipeline20 and only transcripts with values of fragment per kilobase per million of mapped reads (FPKM) higher than 1 were taken into account. The lists obtained with the two specific probes directed to Neat1 (Table 1) were crossed to assess the specificity of the results. 4,268 genes were found associated with paraspeckles, which represented 28% of expressed transcripts in GH4C1 cells13. Consistent with results obtained using qPCR analysis (Figure 5A-C), the transcripts of Gh, Prl, and Malat1 were found to be associated with Neat1. The RNA pull-down method has therefore been proved to be an efficient tool to explore the interaction between lncRNAs and their RNA targets.

Figure 1: Graphical representation of the RNA pull down procedure. On the first day, cells or tissues were cross-linked with paraformaldehyde, lysed, and sonicated before the hybridization step that was performed by adding biotinylated specific probes. Magnetic streptavidin beads were then added to separate specific material from the rest of the cell lysate. On the second day, beads were isolated by a magnet and washed several times. A de-crosslinking step allowed recovery of RNAs that were purified and used for RT-qPCR or RNA-seq analysis. Please click here to view a larger version of this figure.

Figure 2: Secondary structure of a Neat1 sequence (nucleotide 1,480 to 2,000) as predicted by bioinformatics resource (the RNAstructure webserver; lowest free energy structure). The structure is colored according to degree of probability of base pairing. The two oligonucleotides probes (SO1 and SO2) in red are positioned along the Neat1 RNA structure. Please click here to view a larger version of this figure.

Figure 3: qPCR validation of Neat1 enrichment versus input. qPCR validation of Neat1 enrichment versus input after Neat1 RNA pull down by two different specific probes (SO1-rn and SO2-rn for GH4C1 cells and SO1-mm and SO2-mm for pituitary tissue) as compared to a non-specific one (NSO-rn for GH4C1 cells and NSO-mm for pituitary tissue) in GH4C1 rat cells (A) and in mouse pituitary tissue extracts (B). Results are mean ± SEM obtained in 3 to 10 experiments. Please click here to view a larger version of this figure.

Figure 4: qPCR validation of Malat1 and Neat1 enrichment versus input after Malat1 RNA pull down. qPCR validation of Malat1 (A) and Neat1 (B) enrichment versus input after Malat1 RNA pull down by two different specific probes (SO3-rn and SO4-rn) as compared to a non-specific one (NSO-rn) in GH4C1 rat cells. Results are mean ± SEM obtained in 3 experiments. Please click here to view a larger version of this figure.

Figure 5: qPCR validation of Malat1, Gh, Prl enrichment versus input after Neat1 RNA pull down. qPCR validation of Malat1 (A), Gh (B), Prl (C) enrichment versus input after Neat1 RNA pull down using different specific probes as compared to a non-specific one in GH4C1 rat cells and mouse pituitary tissue extracts. Results are mean ± SEM obtained in 3 to 8 experiments. Please click here to view a larger version of this figure.
| PROBE NAMES | Sequences |
| NSO-Rn | TAAAATACCATTTGATGTTTGAAATTAT |
| SO1-Rn | CTCCACCATCATCAATCCTCTGGAC |
| SO2-Rn | GCCTTCCCACATTTAAAAACACAAC |
| SO3-Rn | AACTCGTGGCTCAAGTGAGGTGACA |
| SO4-Rn | AAGACTCTCAGGCTCCTGCTCATTC |
| NSO-mm | GTTTGTGGTTTAACAGTGGGAAGGC |
| SO1-mm | GCCTTCCCACTGTTAAACCACAAAC |
| SO2-mm | CTCACCCGCACCCCGACTCCTTCAA |
| qPCR PRIMERS : | |
| Rattus norvegicus | |
| Neat1 | AAGGCACGAGTTAGCCGCAAAT |
| TGTGCACAGTCAGACCTGTCATTC |
| Malat1 | GAAGGCGTGTACTGCTATGCTGTT |
| TCTCCTGAGGTGACTGTGAACCAA |
| Gh1 | CCGCGTCTATGAGAAACTGAAGGA |
| GGTTTGCTTGAGGATCTGCCCAAT |
| Prl | TGAACCTGATCCTCAGTTTGGT |
| AGCTGCTTGTTTTGTTCCTCAA |
| Mus musculus | |
| Neat1 | TGGGCCCTGGGTCATCTTACTAGATA |
| CACAGCTGTTCCAATGAGCGATCT |
| Gh1 | CTCGGACCGTGTCTATGAGAAACTGA |
| TTTGCTTGAGGATCTGCCCAACAC |
| Prl | TGAACCTGATCCTCAGTTTGGT |
| AGCTGCTTGTTTTGTTCCTCAA |
Table 1: Sequences of DNA oligonucleotide probes and qPCR primers