MODIFICATION OF SMALL RNAS FOR THERAPEUTIC USES
20210269798 · 2021-09-02
Assignee
Inventors
Cpc classification
C12N15/111
CHEMISTRY; METALLURGY
C12N15/113
CHEMISTRY; METALLURGY
C12P19/34
CHEMISTRY; METALLURGY
C12N2320/51
CHEMISTRY; METALLURGY
A61P35/00
HUMAN NECESSITIES
International classification
C12N15/113
CHEMISTRY; METALLURGY
A61P35/00
HUMAN NECESSITIES
Abstract
Provided are methods for improving stability of small therapeutic RNAs by adding one or more non-templated nucleotides such as cytidines and uridines to the 3′ end of the small therapeutic RNAs. Also disclosed are modified small therapeutic RNAs comprising one or more non-templated nucleotides such as cytidines and uridines at the 3′ end and pharmaceutical compositions comprising such modified small therapeutic RNAs.
Claims
1. A method of improving stability of a small RNA molecule comprising adding one or more non-templated nucleotides to the 3′ end of the small RNA molecule.
2. The method of claim 1, comprising contacting the small RNA molecule with a 3′ to 5′ exonuclease to remove 3′ overhang before adding the one or more non-templated nucleotides.
3. The method of claim 1 or claim 2, wherein one, two, three, four, or five non-templated nucleotides are added to the 3′ end of the small RNA molecule.
4. The method of any one of claims 1-3, wherein the non-tem plated nucleotide is cytidine.
5. The method of any one of claims 1-3, wherein the non-tem plated nucleotide is uridine.
6. The method of any one of claims 1-5, wherein the small RNA molecule is an siRNA, an shRNA or a miRNA.
7. The method of any one of claims 1-6, wherein the small RNA molecule is derived from Dicer.
8. The method of any one of claims 1-7, wherein the small RNA molecule has a size of less than 50 bps, less than 45 bps, less than 40 bps, less than 35 bps, less than 30 bps, less than 35 bps, less than 30 bps, less than 25 bps, less than 20 bps, or less than 15 bps.
9. The method of any one of claims 1-8, wherein the small RNA molecule has a size of about 15 bps, about 16 bps, about 17 bps, about 18 bps, about 19 bps, about 20 bps, about 21 bps, about 22 bps, about 23 bps, about 24 bps, about 25 bps, about 26 bps, about 27 bps, about 28 bps, about 29 bps, or about 30 bps.
10. A modified small RNA molecule comprising the nucleotide sequence of an unmodified small RNA molecule, and one or more non-templated nucleotides at the 3′ end of the unmodified small RNA molecule, wherein the modified small RNA molecule has an improved in vivo stability relative to the unmodified small RNA molecule.
11. The modified small RNA molecule of claim 10, comprising one, two, three, four, or five non-templated nucleotides at the 3′ end of the unmodified small RNA molecule.
12. The modified small RNA molecule of claim 10 or claim 11, wherein the non-templated nucleotide is cytidine.
13. The modified small RNA molecule of claim 10 or claim 11, wherein the non-templated nucleotide is uridine.
14. The modified small RNA molecule of any one of claims 10-13, wherein the small RNA molecule is an siRNA, an shRNA or a miRNA.
15. The modified small RNA molecule of any one of claims 10-14, wherein the small RNA molecule is derived from Dicer.
16. The modified small RNA molecule of any one of claims 10-15, wherein the small RNA molecule has a size of less than 50 bps, less than 45 bps, less than 40 bps, less than 35 bps, less than 30 bps, less than 35 bps, less than 30 bps, less than 25 bps, less than 20 bps, or less than 15 bps.
17. The modified small RNA molecule of any one of claims 10-16, wherein the small RNA molecule has a size of about 15 bps, about 16 bps, about 17 bps, about 18 bps, about 19 bps, about 20 bps, about 21 bps, about 22 bps, about 23 bps, about 24 bps, about 25 bps, about 26 bps, about 27 bps, about 28 bps, about 29 bps, or about 30 bps.
18. A pharmaceutical composition comprising the modified small RNA molecule of any one of claims 10-17.
19. A method of treating a disease or condition selected from cancer, a physiological and metabolic disorder, and a viral infection comprising administering to a subject suffering such a disease or condition a therapeutically effective amount of the modified small RNA molecule of any one of claims 10-17 or the pharmaceutical composition of claim 18.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
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DETAILED DESCRIPTION
[0061] Methods of improving the stability of small therapeutic RNAs are provided herein. The method includes adding one or more non-templated nucleotides, such as cytidines and uridines, to the 3′ end of the small therapeutic RNA molecule. Such modified small RNAs can stably bind to Dicer and escape the cell defense system to stably exist in cells for a longer time such that the modified small RNAs can achieve their therapeutic effects. Various small therapeutic RNAs are encompassed by this disclosure. In some embodiments, the small RNAs include, for example, siRNA, shRNA, miRNA, and saRNA. In some embodiments, the small RNAs include Dicer substrate small RNAs, such as Dicer substrate siRNAs (DsiRNAs), which can bind to Dicer and result in increased RNAi activities.
[0062] Adding non-templated nucleotides to the 3′ ends of small RNA molecules can have a profound impact on the stability and biological function of the small RNA molecules. Evidence accumulated over the past few decades has established roles for uridylation and adenylation in small RNA stabilization and degradation. 3′-end formation of small RNAs occurs through a delicate balance between the removal and the addition of nucleotides. By sequencing transfected small RNAs of total RNA and associated with Dicer-containing ribonucleoprotein (RNP), the majority of non-template mono-uridine in 3′ end of small RNAs were demonstrated to be associated with Dicer.
[0063] miRNAs and siRNAs appeared to be distinguished in two primary ways. First, miRNAs were viewed as endogenous and purposefully expressed products of an organism's own genome, whereas siRNAs were thought to be primarily exogenous in origin, derived directly from the virus, transposon, or transgene trigger. Second, miRNAs appeared to be processed from stem-loop precursors with incomplete double-stranded character, whereas siRNAs were found to be excised from long, fully complementary double-stranded RNAs (dsRNAs). Despite these differences, the size similarities and sequence-specific inhibitory functions of miRNAs and siRNAs immediately suggested relatedness in biogenesis and mechanism. As demonstrated herein, EXOD (ERI protein) enriched the siRNA stability. EXOD stimulates the long-term stability of mono-uridylated siRNAs in colon cancer cells. This feature makes mono-uridylated siRNA a more powerful therapeutic agent.
[0064] As demonstrated herein, non-template uridine addition was predominant in Dicer immunoprecipitation with both the selected strand and non-selected strand of the small RNAs. The experimental data shows that the mono-uridylated small RNAs are favorable to Dicer. However, EXOD enriched siRNA stability but not miRNA. Mono-uridine modified siRNA shows the efficiency for a longer term in colorectal cancer, and therefore such modified siRNAs have therapeutic uses in treating cancer.
[0065] As disclosed herein are cytidylated small RNAs which demonstrated improved stability, thereby enhancing the therapeutic effects comparing to unmodified small RNAs. It was demonstrated that small RNAs such as siRNA and CTP were co-localized in the nucleus of the cell.
[0066] For exogenous small RNAs such as siRNAs, the small RNA molecules are modified based on the known sequences of such RNA molecules by adding one or more non-templated nucleotide to the 3′ end of the known sequences. Optionally, the small RNA molecules are treated with an exonuclease to remove the 3′ overhang before cytidylation.
[0067] For endogenous small RNAs such as miRNAs, immunoprecipitation of Dicer or Argonaute complex are performed to recover endogenous small RNAs captured by Dicer or Argonaute. Sequence analysis is performed to determine the sequence of the captured endogenous small RNAs. Based on the obtained sequence, modified small RNAs are produced by adding one or more non-templated cytidines or uridines to the 3′ end of the sequence. Such modified miRNAs are transfected to cells for therapeutic uses.
[0068] The following examples are intended to illustrate various embodiments of the invention. As such, the specific embodiments discussed are not to be construed as limitations on the scope of the invention. It will be apparent to one skilled in the art that various equivalents, changes, and modifications may be made without departing from the scope of invention, and it is understood that such equivalent embodiments are to be included herein. Further, all references cited in the disclosure are hereby incorporated by reference in their entirety, as if fully set forth herein.
EXAMPLES
Example 1: Materials and Methods
[0069] Determination of IC50 value: Generation of the psiCHECK-hnRNPH_AS (antisense reporter) and psiCHECK-hnRNPH_S (sense reporter) vectors used in this study was previously disclosed (Sakurai et al., 2011). HCT116 cells were co-transfected in a 48-well format (50,000 cells/well) with psiCHECK-hnRNPH-AS or psiCHECK-hnRNPH-S vector (50 ng), 3 pM-50 nM small RNAs and 1 μL Lipofectamine 2000 (Invitrogen) per well. Cells were lysed in 1× Passive Lysis Buffer (Promega) 24 hours after transfection and the efficiency and duration of small RNA mediated gene silencing analyzed using the Dual-Luciferase Reporter System (Promega) and a Veritas microplate luminometer (Turner Biosystems). The average was calculated from the replicates to set Renilla/Firefly luciferase expression to 100%. An IC50 curve was generated using Prism 5.01 software (GraphPad). Sigmoidal dose response was calculated according to γ=Bottom+(Top−Bottom)/(1+10)λ((Log EC50−χ)); where χ is the logarithm of concentration and γ is the response.
[0070] For siDicer or siAGO2 treatment, HCT116 cells were seeded in a 24-well plate (100,000 cells/well) and transfected with 20 nM siRNA-targeting Dicer or AGO2. The sequences of the siRNAs used in this study were: Dicer, 5′-UUUGUUGCGAGGCUGAUUCdTdT-3′; AGO2, 5′-GCACGGAAGUCCAUCUGAAdTdT-3′. Twenty-four hours later, the siRNA-treated cells were lysed and used for Dual Luciferase assays and RT-qPCR, respectively. The same procedure described above was used for Dual Luciferase assays.
[0071] Flag-tag immunoprecipitation: HCT116 cell cultures (˜80% confluent) in 10-cm dishes were co-transfected with a Flag-tagged Argonaute or Dicer expression plasmid and each small RNA and incubated for 48 hours. Cells were then washed with ice-cold 1×PBS, followed by incubation (15 minutes) in 1 mL of lysis buffer (10 mM Tris-HCl pH 7.5, 10 mM KCl, 2 mM MgCl.sub.2, 5 mM DTT, 2 M NaCl and 1× Complete EDTA-free protease inhibitor cocktail; Roche). Cells were then scraped off the plate and the suspensions were supplemented with recombinant RNasin (final concentration 0.4 U/μL, Promega). The resulting mixtures were centrifuged for 20 minutes at 13,000 rpm. The supernatant was recovered and centrifuged for 5 minutes at 13,000 rpm. Anti-Flag agarose beads (40 μL; Sigma) were pre-blocked for 2 hours at 4° C. in W1 buffer (0.5% Nonidet P-40, 150 mM NaCl, 2 mM MgCl.sub.2, 2 mM CaCl.sub.2), 20 mM Tris-HCl, pH 7.5, 5 mM DTT and 1× Complete EDTA-free protease inhibitor cocktail) containing 1 mg/mL yeast tRNA and 1 mg/mL BSA. Anti-Flag M2 affinity beads (Sigma) were mixed with the supernatant protein extract according to the manufacturer's recommendations and then incubated (3 hours, 4° C.). The gel was washed with the same buffer, and the beads were resuspended in 3× Flag peptide for elution and incubated (30 minutes, 4° C.). RNAs were eluted from the beads by phenol extraction.
[0072] Small RNA deep sequencing: HCT116 cells were split in 10-cm dish to 70-80% confluency in DMEM media one day prior to transfection. Cells were transfected with the small RNAs (50 nM) using lipofectamine 2000 according to the manufacturer's instructions (Invitrogen). Forty-eight hours after transfection, total RNA was isolated with TriZol reagent (Invitrogen, Carlsbad, Calif.) for Illumina deep sequencing.
[0073] Bioinformatic analysis: To identify the most frequent sense and anti-sense products from each dsiRNA molecule, Novoalign v2.05 (www.novocraft.com) was used to align the sequences generated from Illumina Pipeline v1.6 to the sense and antisense strand of each siRNA molecule. All subsequent analysis was done using the R statistical environment and Bioconductor packages “Biostrings” and “ShortRead” (Morgan et al., 2009). Only sequences that could be aligned to the siRNA sequences without mismatches were retained. The relative start and end position of identified sequences on the siRNA sequence were summarized based on their aligned position and length. The frequency for each product was counted.
[0074] To examine if nucleotides were added at either end of the dicer-processed product, the raw sequences were matched to the siRNA anti-sense sequence with a seed size of 16 after removing the 3′-adapter with Bioconductor package “ShortRead”. For example, for an siRNA sequence length of 23, the Illumina sequences were aligned to 8 seeds, which included the sub-sequence from bases 1-16, 2-17, and so on, of the original siRNA sequence. The matched sequences were then reduced to a set of unique sequences along with the frequencies of occurrence. This set of sequences was then aligned along with the siRNA reference sequence by using the ClustalX2 multiple alignment tool (Larkin et al., 2007) and not allowing gaps. The multiple aligned sequences were visualized and exported with JalView (Waterhouse et al., 2009). Extra bases at either end of the product were highlighted manually.
[0075] Confocal Microscopy: A two-Photon Zeiss LSM510 META Inverted microscope (Carl Zeiss, Jena, Germany) was used. Images were taken with the 40× or 63× water immersion C-APOCHROMAT objective lenses (N.A.=1.2) using multi-track configuration. The following filter sets were used: HFT UV488/543/633 with DBS NFT 490 or NFT 545, HFT KP 650 or mirror or none. An argon laser (488 nm) was used to excite Alexa 488 and emission was collected using a 500-550 nm band pass filter. A helium-neon laser (543 nm) was used to excite Alexa 555 and emission was collected using a 565-615 nm band pass filter. A Ti-Sapphire (Coherent, Inc) laser (790 nm) was used to excite DAPI and emission was collected using a 435-485 nm band pass filter.
[0076] Statistical analysis: All data represent the mean±S.D. Student's t-tests were performed using GraphPad Prism v4 (GraphPad Software).
Example 2: Difference Between miRNA-Mediated Gene Silencing and RNA Stability
[0077] The efficacy of siRNAs targeting the hnRNP H1 mRNA was examined using the sequences shown in
TABLE-US-00001 TABLE 1 Determination of hnRNPH1 small RNAs IC.sub.50 value IC50 [pM] siRNA I siRNA II Antisense strand 89.92 ± 1.206 43.55 ± 1.181 (targeted sense strand) Sense strand 4.278 ± 1.213 77.41 ± 1.228 (targeted antisense strand) AS vs S* 0.05 1.78 S vs AS** 21 0.56 *AS vs S (S preference): IC.sub.50 value of antisense strand/IC.sub.50 value of sense strand; **S vs AS (AS preference): IC.sub.50 value of sense strand/IC.sub.50 value of antisense strand.
[0078] siRNAs targeting hnRNP H1 were tested at concentrations ranging from 0.001 to 50 nM. Asymmetric knockdown of the hnRNP H1 targets by the antisense and sense strands of both types of small RNAs was observed; the antisense strand of small RNAs targeted the sense mRNA strand of hnRNP H1. However, strand bias differed significantly between the siRNA I and II for a given version of these small RNAs. The sense strand of siRNA I (SI) had a 21-fold difference in IC50 value in preference of targeting the antisense mRNA strand of hnRNP H1, while the preference of siRNA II (SII) for targeting the sense mRNA strand of hnRNP H1 was only slightly greater than unity (Table 1 and
[0079] To identify the sequences that interact with AGO2 and DICER, FLAG-tagged AGO2 and DICER were expressed in HCT116 cells by transfection, and cell lysates were subjected to affinity purification with an anti-FLAG bead. Protein and RNA complexes eluted with 3× FLAG peptide, and the purified RNA was identified using deep-sequencing (
[0080] To further investigate the strand selectivity of the four small RNAs tested, an IIlumina GAII sequencer was used to deep-sequence a transfected short RNA library from HCT116 cells. The extracted tags were then mapped to individual small RNAs. In this experiment, the number of reads obtained reflects the relative existence and stability of a given strand species (Table 2).
TABLE-US-00002 TABLE 2 Transfected small RNAs counts number of total RNA, Dicer RNA and Ago2 immunoprecipitation siRNA I siRNA II Total RNA Dicer IP AGO2 IP Total RNA Dicer IP AGO2 IP Total 21,388,815 10,606,494 22,003,133 25,345,783 1,940,450 16,282,902 Reads Matched to 45,542 73,135 1,158,830 405,642 146,281 555,069 AS Matched to 2,853,298 651,505 422,828 419,135 19,040 425,620 S Mapped 2,898,840 724,640 1,581,658 824,777 165,321 980,689 Total % of AS.sup.1 0% 1% 5% 2% 8% 3% % of S.sup.2 13% 6% 2% 2% 1% 3% % mapped 14% 7% 7% 3% 9% 6% to smRNA.sup.3 AS vs S.sup.4 0.0 0.1 2.7 1.0 7.7 1.3 S vs AS.sup.5 62.7 8.9 0.4 1.0 0.1 0.8 .sup.1% of AS: matched to AS × 100/total reads .sup.2% of S: matched to S × 100/total reads .sup.3mapped to smRNA %: mapped total × 100/total reads .sup.4AS vs S (AS preference): % of AS/% of S .sup.5S vs AS (S preference): % of S/% of AS
[0081] To compare the levels of each small RNA in the different samples, lists of the most prevalent species of short RNAs derived from both strands of transfected species were generated. The sequences, normalized counts and percent abundance of transfected small RNAs are shown in Table 2. The mapped total of siRNA I_sense which was the best gene knockdown efficiency in Table 1, had the highest normalized count number of 2,853,298 from lysates of total RNA.
[0082] To compare the antisense and sense strands of transfected small RNAs, the percentage of antisense or sense strands was calculated (
[0083] To understand the uridylation in siRNAs, the percentage of uridylation in each strand of siRNAs from total, Ago2 bound and Dicer bound RNA pools was analyzed (
Example 3: Pattern of Uridylation
[0084] To investigate the association between the extent of U addition and truncation in 3′ end of siRNAs, the siRNA sequences from small RNA deep sequencing data were analyzed (Tables 3-5).
TABLE-US-00003 TABLE 3 U addition from total lysate Number Total Count Percentage of U siRNA I siRNA II siRNA I siRNA II addition GS PS GS PS GS PS GS PS 0 37,694 1,821,412 279,231 388,781 85.3 64.0 69.2 93.2 1 4,516 315,505 27,282 5,561 10.2 11.1 6.8 1.3 2 371 135,974 7,441 954 0.8 4.8 1.8 0.2 3 36 19,737 1,071 91 0.1 0.7 0.3 0.0 4 2 696 48 2 0.0 0.0 0.0 0.0 5 23 1 0.0 0.0 6 1 0.0 42,619 2,293,348 315,074 395,389
TABLE-US-00004 TABLE 4 Ago2 Immunoprecipitation Number Total Count Percentage of U siRNA I siRNA II siRNA I siRNA II addition AS S AS S AS S AS S 0 973,951 297,275 252,018 226,015 91.0 88.4 91.0 73.4 1 95,649 30,650 22,829 70,611 8.9 9.1 8.2 22.9 2 833 7,758 2,053 10,255 0.1 2.3 0.7 3.3 3 63 611 96 1,030 0.0 0.2 0.0 0.3 4 12 6 15 0.0 0.0 0.0 5 1 1 0.0 0.0 0.0 6 1 0.0 1,070,496 336,307 277,003 307,927
TABLE-US-00005 TABLE 5 Dicer Immunoprecipitation Number Total Count Percentage of U siRNA I siRNA II siRNA I siRNA II addition AS S AS S AS S AS S 0 47,100 90,516 30,483 11,506 64.4 13.9 20.8 60.4 1 14,724 115,219 12,677 4,728 20.1 17.7 8.7 24.8 2 1,215 15,843 1,475 285 1.7 2.4 1.0 1.5 3 77 2,148 1 4 0.3 0.0 0.0 4 36 0.0 5 0.0 6 0.0 63,116 223,762 44,636 16,523
[0085] The selected strands of siRNAs were truncated to the last nucleotide of 21 from total RNA (which is transfected siRNAs, collected total RNA and then sequenced). However, it disappeared non-selected strand of siRNAs of SI_AS and SII_S from total RNA (
Example 4: Mono-Uridylated siRNA Affected by Dicer not Ago2
[0086] The impact of Dicer knockdown on uridylated siRNAs affected the activity of small RNA, indicating that Dicer may have affected efficiency of mono-uridylated siRNAs. However, the change of activity in siRNA and mono-uridylated siRNA was insignificant in Ago2-deficient cells; knockdown of Ago2 did not influence upon the activity of siRNA. Thus, Dicer may contribute to activity of mono-uridylated siRNAs (
Example 5: Eri1 Affected Different Functions in miRNAs and siRNAs
[0087] Uridylation of siRNA might degrade with 3′ to 5′ exonuclease of Eri1. Therefore, the effect of human Eri1 was tested, using Eri-1 knockdown HCT116. Next, the miRNA abundance and/or distribution and uridylation bound with Dicer was tested. 3′ uridylation of mature miRNA was reported to modulate the stability of small RNAs (Gutierrez-Vazquez et al., 2017). The normalized counts were significantly reduced in Dicer bound small RNAs. A global downregulation of miRNA was detected between negative control and Dicer bound miRNA when miRNA count distributions were analyzed with Kolmogorov Smirnoff test (
[0088] To determine the 3′ exonuclease involved in miRNAs and siRNA biogenesis, Eri1 knockdown was generated by transfecting siRNA mixtures into HCT116 (
[0089] Next, whether Eri1 had any effect on the uridylation of miRNAs and siRNA was determined. A global up-regulation of uridylated miRNA was detected in Eri1 mutants (
Example 6: Potential Mechanism of Eri1-Mediated Effects on smRNA Stability
[0090] To understand the function of uridylation underlying Eri1 and Dicer in miRNAs, the relative miRNA expression levels were characterized by dividing the read number of miRNA with siEri1 by that of total miRNA(-control) [Log 2(normalized counts of miRNAs in absent of Eri1/normalized counts of miRNA in total RNA fraction)] of an individual examination of each miRNA (
[0091] In contrast, the total normalized counts of miRNAs in the siEri1 treated cell seemed to be decreased miRNAs when analyzed globally (
[0092] The stability of many miRNAs (545 miRNAs) was increased in Eri1 defected cells (
[0093] A significant increment of miRNA uridylation was observed when treated with siEri1. The percentage of U addition of global miRNA was analyzed to investigate the change of miRNA upon knockdown of Eri1 (
[0094] If Eri1 exonuclease acts in separate pathways, the uridylated miRNAs should differ in up-regulated and down-regulated miRNAs by Eri1. The uridylation fraction of individual miRNA to grouped up-regulation (>1: more than 2-fold) or down-regulation (<−1: less than 2-fold) in Eri1-deleted cells depend on
[0095] To understand the mechanism uridylated miRNA biogenesis with Dicer, the uridylated miRNAs in Eri1 knockdown cells were reclassified into Dicer favor and disfavor. The expression level of miRNA bound to Dicer was determined by Dicer immunoprecipitation (
Example 7: Cytidylated smRNAs Stability
[0096] This example demonstrates that cytidylated smRNAs such as siRNAs have improved stability and can be used as therapeutic agents.
[0097] Similar to Example 3, the number of cytidine in the 3′ end of siRNAs was analyzed and summarized in Table 6 below.
TABLE-US-00006 TABLE 6 C addition in the 3′ end of siRNAs Number of C Total Count Percentage addition DsiRNA I DsiRNA II siRNA I siRNA II DsiRNA I DsiRNA II siRNA I siRNA II 0 37,694 203,158 90,516 30,483 19.193 17.232 13.893 20.839 1 58,590 55,206 129,647 7,732 29.833 4.683 19.900 5.286 2 24,528 751,934 260,320 85,310 12.489 63.779 39.957 58.319 3 983 551 1,736 43 0.501 0.047 0.266 0.029 4 4 4 12 0.002 0.000 0.002 5 5 0.001 6 1 0.000
Example 8: Effects of siRNAs on Tumor Model
[0098] Xenograft colon cancer model in balb-c mice was generated and treated with siRNA, CC-added siRNA and U added siRNA. The siRNAs were injected on Day 2.
TABLE-US-00007 TABLE 7 Tumor reduction by siRNAs Day Day Tumor Day siRNA 1 2 volume 4 1 Male_No_P siRNA_U 0.0539 0.625 0.6*0.6 0.108 [142 ng/g] 2 Female_1P_L siRNA 0.216 0.216 1.2*1.5 1.08 3 Female_1P_R siRNA_CC 0.294 1.008 1.5*2 2.25 4 Female_2P_L siRNA_U 0.294 0.567 1.5*0.8 0.48 5 Female_2P_R saline 0.368 0.907 2*1.3 1.69
REFERENCES
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