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Reverse Transcription

Reverse transcription is a fundamental molecular biology technique that enables the conversion of RNA into complementary DNA (cDNA) using the enzyme reverse transcriptase.
This process is essential for studying gene expression, detecting viral infections, and investigating various biological processes.
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Most cited protocols related to «Reverse Transcription»

The expression levels of human family with sequence similarity 73, member B (FAM73B) and GAPDH genes in limited dilution samples (1:10, 1:100, and 1:1000) were analyzed using qPCR. GAPDH was used as an internal control. Referring to the study design in Table 1, FAM73B is the target gene, and GAPDH is the reference gene. The original sample without any dilution is the reference, and a 1:10, 1:100, and 1:1000 dilution of the original sample are the target samples. There are 6 replicates in each combination of gene and dilution. The gene-specific primers were as follows: hgapdh-5′-ATGGAAATCCCATCACCATCTT-3′ and hgapdh-5′-CGCCCCACTTGATTTTGG-3′; hfam73b-5′-CTCCTGCAGGTGGTAGGC-3′ and hfam73b-5′-CAGAGACTGCATCAGAGCCA-3′. mRNA was extracted from human hepatoma (Huh7) cells and used as a template for reverse transcription by superscript III reverse transcriptase purchased from Invitrogen (Carlsbad, CA). All qPCR experiments were performed using the Applied Biosystems Stepone and StepOnePlus Real-Time system (Perkin-Elmer Applied Biosystems). All the amplifications were done using SYBR Green PCR Master Mix (Applied Biosystems). The thermal cycling conditions included an initial denaturation step at 95°C for 10 min, followed by 40 cycles at 95°C for 30s, 60°C for 30s, and 72°C for 30s. Melting curve analysis of every qPCR was conducted after each cycle.
In this study, we try to improve the 2-ΔΔCT method. Our method, called the individual efficiency–corrected calculation method, is shown in Table 2. Unlike the 2-ΔΔCT method, our method accounts for individual efficiencies of samples. We computed the amplification rate E (1 + efficiency) for each sample (Table 2, Eqs. 1-5). Specifically, the method was based on an exponential function, and background fluorescence was included in this function (Eq. 1). Then we took the difference between two consecutive PCR cycles by subtracting the fluorescence of the former cycle from that of the later cycle (Eq. 2). Therefore, the data with n cycles were transformed to data with n−1 cycles. Importantly, background fluorescence was removed. After that, a simple linear regression model (Eq. 4) was applied to the log-transformed equation (Eq. 3). The parameter (β1) estimated using linear regression can be used to calculate E (Eq. 5). To calculate the starting DNA amount (x0), we need to find out the new threshold cycle, CT', and we set the new threshold to T/2 (Eqs. 2 and 6). The fold change of gene expression level was calculated as the relative DNA amount of a target gene in a target sample and a reference sample, normalized to a reference gene (Eq. 7). The DNA amounts of a reference gene in reference and target samples are denoted as x0,A and x0,B, and the amounts of a target gene in the two groups are denoted as x0,C and x0,D, respectively. The derivation of CT' was based on the equal-ratio property of the difference value zk and the cycle m, which is an integer cycle right before CT' (Eqs. 8-9). The fluorescence value zm should be less than the new threshold T/2 because the selected data points had monotone increasing values of zk.
For the 2-ΔΔCT method, we directly used the threshold cycle values automatically generated by the qPCR system. For the individual efficiency corrected calculation method, we selected four successive cycles for every PCR run, the first three of which have the fluorescence values below the threshold and the last of which has a fluorescence value larger than the threshold. Therefore, the target cycles are the rounded threshold cycle and the former three cycles, or the rounded threshold cycle and the former two cycles plus the latter one.
In the individual efficiency corrected calculation method, we calculated PCR amplification efficiency for every sample. To reduce potential variation, we then took the mean of the efficiencies for the 6 replicates under each condition, which is a combination of gene and dilution. Hence, the 6 replicates had the same efficiency for further calculation, but each combination (for example, the combination of FAM73B and a 1:10 dilution) had a different efficiency.
Because the 2-ΔΔCT method and our method are relative quantification strategies, it is difficult to assess their accuracy. This is why we planned to use a series of dilutions of the original sample to evaluate the accuracy of these two methods based on the pattern of the estimates. According to the experimental design, there were two trends in the estimates. First, for each gene, the ratios of the initial DNA amount were 1, 1:10 (0.1), 1:100 (0.01), and 1:1000 (0.001), corresponding to the four dilution conditions. The second trend was that the relative gene amounts (FAM73B/GAPDH) with respect to the four dilution conditions were the same, with a ratio of 1: 1: 1: 1 if the original sample without dilution was set to 1. The precision of the methods was then analyzed by computing coefficients of variation (CVs). The equation is:
where s and are the standard deviation and the mean of the 6 replicates in each combination of gene and dilution.
Publication 2013
Fluorescence GAPDH protein, human Gene Expression Genes Genes, vif Hepatocellular Carcinomas Homo sapiens Oligonucleotide Primers Reverse Transcription RNA, Messenger RNA-Directed DNA Polymerase SYBR Green I Technique, Dilution Transcriptase Transcription, Genetic
SpecificityFluorophoreCloneNote
CD3AF488UCHT110uL of antibody used
CD8APC-Cy7SK1
CD4AF700RPA-T4
CD57PEQA17A04
CD56APC5.1H11
CD103BV421Ber-ACT8
Integrin 7PEFIB504
CD49aAPCTS2/7BioLegend
CD43PECD43-10G7BioLegend
Gating conditions for each of the validation experiments are shown in Figures 4D and 4E.
Post sorting, samples were each split into quintuplicates, and then cleaned up with 2x SPRI. Samples were then brought into reverse transcription in an adaptation of SMARTseq2 (Picelli et al., 2014 (link)) and SCRB-seq (Soumillon et al., 2014 (link)) as described here: https://dx.doi.org/10.17504/protocols.io.nkgdctw.
The pooled library was sequenced on an Illumina Nextseq (50 R1, 8 index, 34 R2). Post base calling, samples were aligned using a wrapper for DropSeqTools against the human reference hg19 to generate RNA counts matrices.
To assess the agreement between single-cell datasets and bulk-sorted experiments, we examined the top DE genes separating our gated populations in the CITE-seq reference dataset. We next visualized the relative expression of these genes in the heatmaps in Figures 4D and 4E. The bulk-sorted populations exhibited highly concordant relative expression patterns for DE genes as we observed in CITE-seq data.
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Publication 2021
Acclimatization Dietary Fiber DNA Library Gene Expression Genes Homo sapiens Immunoglobulins Population Group Reverse Transcription
After flow sorting, single cells were captured on the Fluidigm C1 Single-Cell Auto Prep System (C1), lysed on chip, and subjected to reverse transcription and cDNA amplification using the SMARTer Ultra Low Input RNA Kit for C1 System (Clontech, Mountain View, CA). Sequencing libraries were prepared using the Nextera XT DNA Library Preparation Kit (Illumina, San Diego, CA) according to C1 protocols (Fluidigm). Barcoded libraries were pooled and quantified using a Qubit Fluorometer (Thermo Scientific Life Technologies, Grand Island, NY). Single-read sequencing of the pooled libraries was carried out either on a HiScanSQ or a HiSeq2500 sequencer (Illumina) with 100-base reads, using TruSeq v3 Cluster and SBS kits (Illumina) with a target depth of >2.5 M reads. Sequences were aligned to the UCSC Human Genome Assembly version 19, gene expression levels quantified using RSEM [28 (link)], and TPM values loaded into R [29 (link)] for analyses. See Additional file 1 for more details on data processing procedures.
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Publication 2015
Cells DNA, Complementary DNA Chips DNA Library Gene Expression Genome, Human Reverse Transcription
Thirty hearts of chicken embryos of 3 days of development were isolated and separated into the five different compartments, i.e. sinus venosus (SV), atrium (A), atrioventricular canal (AVC), ventricle (V) and outflow tract (OFT). Post-mortem cortical brain tissue of eight control persons and 10 Huntington disease patients was obtained from Prof Dr R.A.C. Roos (Leiden University, the Netherlands). Total RNA was isolated using RNAeasy columns (Qiagen) according to the manufacturer's instructions. The total RNA was treated with DNase RQ1 (Promega) and the integrity of the RNA was checked using the BioAnalyzer and the Agilent RNA 6000 Nano kit (II). A 1–0.5 µg total RNA was converted into cDNA using an anchored poly-dT primer and the Superscript II (human samples) or III (chicken samples) Reverse transcription kit (Invitrogen).
Publication 2009
Autopsy Brain Cerebral Ventricles Chickens Common atrioventricular canal Cortex, Cerebral Deoxyribonucleases DNA, Complementary Embryonic Development Heart Heart Atrium Homo sapiens Huntington Disease Oligonucleotide Primers Patients Poly T Promega Reverse Transcription Sinuses, Nasal Tissues

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Publication 2019
Bone Marrow Cells Buffers CD4 Positive T Lymphocytes CD8-Positive T-Lymphocytes Cells Clone Cells DAPI Dietary Fiber Division, Cell DNA, Complementary Edetic Acid Fluorescein-5-isothiocyanate Genes Immunoglobulins Love Population Group Reverse Transcription RNA-Seq

Most recents protocols related to «Reverse Transcription»

Example 17

To further validate the activity of the DMPK siRNAs, many of the sequences that showed the best activity in the initial screen were selected for a follow-up evaluation in dose response format. Once again, two human cell lines were used to assess the in vitro activity of the DMPK siRNAs: first, SJCRH30 human rhabdomyosarcoma cell line; and second, Myotonic Dystrophy Type 1 (DM1) patient-derived immortalized human skeletal myoblasts. The selected siRNAs were transfected in a 10-fold dose response at 100, 10, 1, 0.1, 0.01, 0,001, and 0.0001 nM final concentrations or in a 9-fold dose response at 50, 5.55556, 0.617284, 0.068587, 0.007621, 0.000847, and 0.000094 nM final concentrations. The siRNAs were formulated with transfection reagent Lipofectamine RNAiMAX (Life Technologies) according to the manufacturer's “forward transfection” instructions. Cells were plated 24 h prior to transfection in triplicate on 96-well tissue culture plates, with 8500 cells per well for SJCRH30 and 4000 cells per well for DM1 myoblasts. At 48 h (SJCRH30) or 72 h (DM1 myoblasts) post-transfection cells were washed with PBS and harvested with TRIzol® reagent (Life Technologies). RNA was isolated using the Direct-zol-96 RNA Kit (Zymo Research) according to the manufacturer's instructions. 10 μl of RNA was reverse transcribed to cDNA using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems) according to the manufacturer's instructions. cDNA samples were evaluated by qPCR with DMPK-specific and PPIB-specific TaqMan human gene expression probes (Thermo Fisher) using TaqMan® Fast Advanced Master Mix (Applied Biosystems). DMPK values were normalized within each sample to PPIB gene expression. The quantification of DMPK downregulation was performed using the standard 2−ΔΔCt a method. All experiments were performed in triplicate, with Tables 16A-B, 17A-B, and 18A-B presenting the mean values of the triplicates as well as the calculated IC50 values determined from fitting curves to the dose-response data by non-linear regression.

TABLE 16A
sense strandSEQantisense strandSEQ
sequence (5′-3′)IDsequence (5′-3′)ID
ID #1Passenger Strand (PS)NO:Guide Strand (GS)NO:
535GGGCGAGGUGUCGUGCUUA9349UAAGCACGACACCUCGCCC12053
584GACCGGCGGUGGAUCACGA9398UCGUGAUCCACCGCCGGUC12102
716AUGGCGCGCUUCUACCUGA9530UCAGGUAGAAGCGCGCCAU12234
1028CAGACGCCCUUCUACGCGA9842UCGCGUAGAAGGGCGUCUG12546
1276UUUCGAAGGUGCCACCGAA10090UUCGGUGGCACCUUCGAAA12794
1825UGCUCCUGUUCGCCGUUGA10639UCAACGGCGAACAGGAGCA13343
1945CCCUAGAACUGUCUUCGAA10759UUCGAAGACAGUUCUAGGG13463
2529CUUCGGCGGUUUGGAUAUA11343UAUAUCCAAACCGCCGAAG14047
2558GUCCUCCGACUCGCUGACA11372UGUCAGCGAGUCGGAGGAC14076
2628CCGACAUUCCUCGGUAUUA11442UAAUACCGAGGAAUGUCGG14146
2636CCUCGGUAUUUAUUGUCUA11450UAGACAAUAAAUACCGAGG14154
119mer position in NM_001288766.1

TABLE 16B
IC50
ID #1qPCR2qPCR3qPCR4qPCR5qPCR6qPCR7qPCR8(nM)
535111.9105.4106.382.436.729.535.70.165
58490.590.284.767.838.025.828.30.190
71688.985.281.962.032.619.320.30.181
102888.581.883.061.332.727.331.50.127
127687.085.084.066.140.534.036.40.150
182585.185.983.769.136.225.225.00.259
194585.081.774.444.922.917.717.20.070
252983.381.875.350.624.617.517.70.103
255884.381.174.345.423.413.311.80.088
262885.384.079.559.830.323.525.10.140
263686.386.974.344.019.812.413.00.070
2SJCRH30; 0.0001 nM; % DMPK mRNA
3SJCRH30; 0.001 nM; % DMPK mRNA
4SJCRH30; 0.01 nM; % DMPK mRNA
5SJCRH30; 0.1 nM; % DMPK mRNA
6SJCRH30; 1 nM; % DMPK mRNA
7SJCRH30; 10 nM; % DMPK mRNA
8SJCRH30; 100 nM; % DMPK mRNA

TABLE 17A
sense strandSEQantisense strandSEQ
sequence (5′-3′)IDsequence (5′-3′)ID
ID #1Passenger Strand (PS)NO:Guide Strand (GS)NO:
2600CAAUCCACGUUUUGGAUGA11414UCAUCCAAAACGUGGAUUG14118
2636CCUCGGUAUUUAUUGUCUA11450UAGACAAUAAAUACCGAGG14154
2675CCCCGACCCUCGCGAAUAA11489UUAUUCGCGAGGGUCGGGG14193
2676CCCGACCCUCGCGAAUAAA11490UUUAUUCGCGAGGGUCGGG14194
2679GACCCUCGCGAAUAAAAGA11493UCUUUUAUUCGCGAGGGUC14197
2680ACCCUCGCGAAUAAAAGGA11494UCCUUUUAUUCGCGAGGGU14198
2681CCCUCGCGAAUAAAAGGCA11495UGCCUUUUAUUCGCGAGGG14199
2682CCUCGCGAAUAAAAGGCCA11496UGGCCUUUUAUUCGCGAGG14200
119mer position in NM_001288766.1

TABLE 17B
IC50
ID #1qPCR2qPCR3qPCR4qPCR5qPCR6qPCR7(nM)
2600107.5107.6108.1106.3103.172.731.31
263681.181.174.047.225.711.50.073
267588.188.384.364.638.120.70.151
267688.978.984.472.744.935.60.204
267984.087.382.753.331.413.50.091
268087.485.385.168.544.539.60.110
268187.085.477.649.626.516.00.061
268282.483.977.150.827.331.10.047
2SJCRH30; 0.000094 nM; % DMPK mRNA
3SJCRH30; 0.000847 nM; % DMPK mRNA
4SJCRH30; 0.007621 nM; % DMPK mRNA
5SJCRH30; 0.068587 nM; % DMPK mRNA
6SJCRH30; 0.617284 nM; % DMPK mRNA
7SJCRH30; 5.55556 nM; % DMPK mRNA

TABLE 18A
sense strandSEQantisense strandSEQ
sequence (5′-3′)IDsequence (5′-3′)ID
ID #1Passenger Strand (PS)NO:Guide Strand (GS)NO:
584GACCGGCGGUGGAUCACGA9398UCGUGAUCCACCGCCGGUC12102
716AUGGCGCGCUUCUACCUGA9530UCAGGUAGAAGCGCGCCAU12234
1265UUUACACCGGAUUUCGAAA10079UUUCGAAAUCCGGUGUAAA12783
1297AUGCAACUUCGACUUGGUA10111UACCAAGUCGAAGUUGCAU12815
1945CCCUAGAACUGUCUUCGAA10759UUCGAAGACAGUUCUAGGG13463
1960CGACUCCGGGGCCCCGUUA10774UAACGGGGCCCCGGAGUCG13478
2529CUUCGGCGGUUUGGAUAUA11343UAUAUCCAAACCGCCGAAG14047
2530UUCGGCGGUUUGGAUAUUA11344UAAUAUCCAAACCGCCGAA14048
2531UCGGCGGUUUGGAUAUUUA11345UAAAUAUCCAAACCGCCGA14049
2554CCUCGUCCUCCGACUCGCA11368UGCGAGUCGGAGGACGAGG14072
2628CCGACAUUCCUCGGUAUUA11442UAAUACCGAGGAAUGUCGG14146
2629CGACAUUCCUCGGUAUUUA11443UAAAUACCGAGGAAUGUCG14147
2681CCCUCGCGAAUAAAAGGCA11495UGCCUUUUAUUCGCGAGGG14199
119mer position in NM_001288766.1

TABLE 18B
IC50
ID #1qPCR2qPCR3qPCR4qPCR5qPCR6qPCR7(nM)
58490.877.097.771.945.029.70.228
71696.582.577.064.643.333.90.080
126568.580.968.057.137.525.70.146
129771.467.269.453.540.525.40.171
194571.862.341.729.822.415.30.006
196063.065.462.145.831.128.30.068
252963.558.749.231.122.921.90.017
253069.366.753.143.238.824.50.016
253169.972.457.340.235.425.60.018
255468.270.151.243.032.117.30.043
262869.767.962.538.431.617.10.042
262972.165.669.042.134.413.70.078
268182.491.587.655.529.319.60.084
2DM1 myoblasts; 0.000094 nM; % DMPK mRNA
3DM1 myoblasts; 0.000847 nM; % DMPK mRNA
4DM1 myoblasts; 0.007621 nM; % DMPK mRNA
5DM1 myoblasts; 0.068587 nM; % DMPK mRNA
6DM1 myoblasts; 0.617284 nM; % DMPK mRNA
7DM1 myoblasts; 5.55556 nM; % DMPK mRNA

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Patent 2024
Cell Lines Cells DNA, Complementary Down-Regulation Gene Expression Homo sapiens Lipofectamine Myoblasts Myoblasts, Skeletal Myotonic Dystrophy NM-107 Patients PPIB protein, human Reverse Transcription Rhabdomyosarcoma RNA, Messenger RNA, Small Interfering Tissues Transfection trizol

Example 24

For groups 1-12, see study design in FIG. 32, the 21mer Atrogin-1 guide strand was designed. The sequence (5′ to 3′) of the guide/antisense strand was UCGUAGUUAAAUCUUCUGGUU (SEQ ID NO: 14237). The guide and fully complementary RNA passenger strands were assembled on solid phase using standard phospharamidite chemistry and purified over HPLC. Base, sugar and phosphate modifications that are well described in the field of RNAi were used to optimize the potency of the duplex and reduce immunogenicity. Purified single strands were duplexed to get the double stranded siRNA described in figure A. The passenger strand contained two conjugation handles, a C6-NH2 at the 5′ end and a C6-SH at the 3′ end. Both conjugation handles were connected to siRNA passenger strand via phosphodiester-inverted abasic-phosphodiester linkers. Because the free thiol was not being used for conjugation, it was end capped with N-ethylmaleimide.

For groups 13-18 see study design in FIG. 32, a 21mer negative control siRNA sequence (scramble) (published by Burke et al. (2014) Pharm. Res., 31(12):3445-60) with 19 bases of complementarity and 3′ dinucleotide overhangs was used. The sequence (5′ to 3′) of the guide/antisense strand was UAUCGACGUGUCCAGCUAGUU (SEQ ID NO: 14228). The same base, sugar and phosphate modifications that were used for the active MSTN siRNA duplex were used in the negative control siRNA. All siRNA single strands were fully assembled on solid phase using standard phospharamidite chemistry and purified over HPLC. Purified single strands were duplexed to get the double stranded siRNA. The passenger strand contained two conjugation handles, a C6-NH2 at the 5′ end and a C6-SH at the 3′ end. Both conjugation handles were connected to siRNA passenger strand via phosphodiester-inverted abasic-phosphodiester linker. Because the free thiol was not being used for conjugation, it was end capped with N-ethylmaleimide.

Antibody siRNA Conjugate Synthesis Using Bis-Maleimide (BisMal) Linker

Step 1: Antibody Reduction with TCEP

Antibody was buffer exchanged with 25 mM borate buffer (pH 8) with 1 mM DTPA and made up to 10 mg/ml concentration. To this solution, 4 equivalents of TCEP in the same borate buffer were added and incubated for 2 hours at 37° C. The resultant reaction mixture was combined with a solution of BisMal-siRNA (1.25 equivalents) in pH 6.0 10 mM acetate buffer at RT and kept at 4° C. overnight. Analysis of the reaction mixture by analytical SAX column chromatography showed antibody siRNA conjugate along with unreacted antibody and siRNA. The reaction mixture was treated with 10 EQ of N-ethylmaleimide (in DMSO at 10 mg/mL) to cap any remaining free cysteine residues.

Step 2: Purification

The crude reaction mixture was purified by AKTA Pure FPLC using anion exchange chromatography (SAX) method-1. Fractions containing DAR1 and DAR2 antibody-siRNA conjugates were isolated, concentrated and buffer exchanged with pH 7.4 PBS.

Anion Exchange Chromatography Method (SAX)-1.

Column: Tosoh Bioscience, TSKGel SuperQ-5PW, 21.5 mm ID×15 cm, 13 um

Solvent A: 20 mM TRIS buffer, pH 8.0; Solvent B: 20 mM TRIS, 1.5 M NaCl, pH 8.0; Flow Rate: 6.0 ml/min

Gradient:

a.% A% BColumn Volume
b.10001
c.81190.5
d.505013
e .40600.5
f.01000.5
g.10002

Anion Exchange Chromatography (SAX) Method-2

Column: Thermo Scientific, ProPac™ SAX-10, Bio LC™, 4×250 mm

Solvent A: 80% 10 mM TRIS pH 8, 20% ethanol; Solvent B: 80% 10 mM TRIS pH 8, 20% ethanol, 1.5 M NaCl; Flow Rate: 0.75 ml/min

Gradient:

a.Time% A% B
b.0.09010
c.3.009010
d.11.004060
e.14.004060
f.15.002080
g.16.009010
h.20.009010

Step-3: Analysis of the Purified Conjugate

The purity of the conjugate was assessed by analytical HPLC using anion exchange chromatography method-2 (Table 22).

TABLE 22
SAX retention% purity
Conjugatetime (min)(by peak area)
TfR1-Atrogin-1 DAR19.299
TfR1-Scramble DAR18.993

In Vivo Study Design

The conjugates were assessed for their ability to mediate mRNA downregulation of Atrogin-1 in muscle (gastroc) in the presence and absence of muscle atrophy, in an in vivo experiment (C57BL6 mice). Mice were dosed via intravenous (iv) injection with PBS vehicle control and the indicated ASCs and doses, see FIG. 32. Seven days post conjugate delivery, for groups 3, 6, 9, 12, and 15, muscle atrophy was induced by the daily administration via intraperitoneal injection (10 mg/kg) of dexamethasone for 3 days. For the control groups 2, 5, 8, 11, and 14 (no induction of muscle atrophy) PBS was administered by the daily intraperitoneal injection. Groups 1, 4, 7, 10, and 13 were harvested at day 7 to establish the baseline measurements of mRNA expression and muscle weighted, prior to induction of muscle atrophy. At three days post-atrophy induction (or 10 days post conjugate delivery), gastrocnemius (gastroc) muscle tissues were harvested, weighed and snap-frozen in liquid nitrogen. mRNA knockdown in target tissue was determined using a comparative qPCR assay as described in the methods section. Total RNA was extracted from the tissue, reverse transcribed and mRNA levels were quantified using TaqMan qPCR, using the appropriately designed primers and probes. PPIB (housekeeping gene) was used as an internal RNA loading control, results were calculated by the comparative Ct method, where the difference between the target gene Ct value and the PPIB Ct value (ΔCt) is calculated and then further normalized relative to the PBS control group by taking a second difference (ΔΔCt).

Quantitation of tissue siRNA concentrations was determined using a stem-loop qPCR assay as described in the methods section. The antisense strand of the siRNA was reverse transcribed using a TaqMan MicroRNA reverse transcription kit using a sequence-specific stem-loop RT primer. The cDNA from the RT step was then utilized for real-time PCR and Ct values were transformed into plasma or tissue concentrations using the linear equations derived from the standard curves.

Results

The data are summarized in FIG. 33-FIG. 35. The Atrogin-1 siRNA guide strands were able to mediate downregulation of the target gene in gastroc muscle when conjugated to an anti-TfR mAb targeting the transferrin receptor, see FIG. 33. Increasing the dose from 3 to 9 mg/kg reduced atrophy-induced Atrogin-1 mRNA levels 2-3 fold. The maximal KD achievable with this siRNA was 80% and a tissue concentration of 40 nM was needed to achieve maximal KD in atrophic muscles. This highlights the conjugate delivery approach is able to change disease induce mRNA expression levels of Atrogin-1 (see FIG. 34), by increasing the increasing the dose. FIG. 35 highlights that mRNA down regulation is mediated by RISC loading of the Atrogin-1 guide strands and is concentration dependent.

Conclusions

In this example, it was demonstrated that a TfR1-Atrogin-1 conjugates, after in vivo delivery, mediated specific down regulation of the target gene in gastroc muscle in a dose dependent manner. After induction of atrophy the conjugate was able to mediate disease induce mRNA expression levels of Atrogin-1 at the higher doses. Higher RISC loading of the Atrogin-1 guide strand correlated with increased mRNA downregulation.

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Patent 2024
Acetate Anions Antibody Formation Antigens Atrophy Biological Assay Borates Buffers Carbohydrates Chromatography Complementary RNA Complement System Proteins Cysteine Dexamethasone Dinucleoside Phosphates DNA, Complementary Down-Regulation Ethanol Ethylmaleimide Freezing Genes Genes, Housekeeping High-Performance Liquid Chromatographies Immunoglobulins Injections, Intraperitoneal maleimide MicroRNAs Mus Muscle, Gastrocnemius Muscle Tissue Muscular Atrophy Nitrogen Obstetric Delivery Oligonucleotide Primers Pentetic Acid Phosphates Plasma PPIB protein, human Prospective Payment Assessment Commission Real-Time Polymerase Chain Reaction Retention (Psychology) Reverse Transcription RNA, Messenger RNA, Small Interfering RNA-Induced Silencing Complex RNA Interference Sodium Chloride Solvents Stem, Plant STS protein, human Sulfhydryl Compounds Sulfoxide, Dimethyl TFRC protein, human Tissues Transferrin tris(2-carboxyethyl)phosphine Tromethamine
Not available on PMC !

Example 6

The efficacy of model compound UBX1967 was studied in the mouse oxygen-induced retinopathy (OIR) model, which provides an in vivo model of retinopathy of prematurity (ROP) and diabetic retinopathy.

C57Bl/6 mouse pups and their CD1 foster mothers were exposed to a high oxygen environment (75% 02) from postnatal day 7 (P7) to P12. At P12, animals were injected intravitreally with 1 μl test compound (200, 20, or 2 uM) formulated in 1% DMSO, 10% Tween-80, 20% PEG-400, and returned to room air until P17. Eyes were enucleated at P17 and retinas dissected for either vascular staining or qRT-PCR. To determine avascular or neovascular area, retinas were flatmounted, and stained with isolectin B4 (IB4) diluted 1:100 in 1 mM CaCl2. For quantitative measurement of senesecence markers (e.g., Cdkn2a, Cdkn1a, 116, Vegfa), qPCR was performed. RNA was isolated and cDNA was generated by reverse-transcription, which was used for qRT-PCR of the selected transcripts.

FIGS. 9A and 9B show that intravitreal (IVT) administration UBX1967 resulted in statistically significant improvement in the degree of neovascularization and vaso-obliteration at all dose levels.

FIGS. 10A and 10B show the relative abundance of several transcripts associated with senescence (p16, pai1) and human disease (vegf). Treatment with UBX1967 resulted in a 58%, 35%, and 24% reduction in p16, pai1, and vegf, respectively. Senescence-associated β-galactosidase (SA-BGal) activity was reduced by 17% after administration of UBX1967.

These results show that a single ocular injection of UBX1967 can functionally inhibit pathogenic angiogenesis and promote vascular repair in this key OIR disease model. We believe that efficacy of UBX1967 in the OIR model is due to elimination of senescent cells and accompanying SASP that propagates senescence in retinal cells and promotes neovascularization of retinal vessels.

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Patent 2024
Aftercare angiogen Animal Model Animals beta-Galactosidase Blood Vessel Cardiac Arrest CDKN1A protein, human Cellular Senescence Diabetic Retinopathy DNA, Complementary Eye Figs Homo sapiens Isolectins Mice, Inbred C57BL Mothers Mus Oxygen pathogenesis Pathologic Neovascularization polyethylene glycol 400 Retina Retinal Diseases Retinal Neovascularization Retinal Vessels Retinopathy of Prematurity Reverse Transcription SERPINE1 protein, human Sulfoxide, Dimethyl Tween 80 TXN protein, human Vascular Diseases Vascular Endothelial Growth Factors Vision

Example 18

The selected siRNAs were transfected at 100, 10, 1, 0.1, 0.01, 0,001, and 0.0001 nM final concentrations into C2C12 mouse muscle myoblasts (ATCC® CRL-1772™). The siRNAs were formulated with transfection reagent Lipofectamine RNAiMAX (Life Technologies) according to the manufacturer's “forward transfection” instructions. Cells were plated 24 h prior to transfection in triplicate on 96-well tissue culture plates, with 4000 cells per well for C2C12 seeding. At 48 h post-transfection cells were washed with PBS and harvested with TRIzol® reagent (Life Technologies). RNA was isolated using the Direct-zol-96 RNA Kit (Zymo Research) according to the manufacturer's instructions. 10 μl of RNA was reverse transcribed to cDNA using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems) according to the manufacturer's instructions. cDNA samples were evaluated by qPCR with DMPK-specific and PPIB-specific TaqMan mouse gene expression probes (Thermo Fisher) using TaqMan® Fast Advanced Master Mix (Applied Biosystems). DMPK values were normalized within each sample to PPIB gene expression. The quantification of DMPK downregulation was performed using the standard 2−ΔΔCt method. All experiments were performed in triplicate, with the results shown in FIG. 17. Four DMPK siRNAs (the numbers indicated in the FIG. 17 legend correspond to the ID # that is listed in Table 19 (Tables 19A-19B)) were shown to effectively cross-react with mouse DMPK mRNA, producing robust mRNA knockdown in the mouse C2C12 myoblast cell line. Two of the siRNAs (ID #s 535 and 1028) were slightly less effective and only produced approximately 70% maximum mRNA knockdown. Two of the siRNAs (ID #s 2628 and 2636) were more effective and produced approximately 90% maximum mRNA knockdown.

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Patent 2024
Cell Lines Cells Cross Reactions DNA, Complementary Down-Regulation Gene Expression Lipofectamine Mus Muscle Tissue Myoblasts PPIB protein, human Reverse Transcription RNA, Messenger RNA, Small Interfering Tissues Transfection trizol
Not available on PMC !

Example 2

Another example of a suitable vector is a retroviral vector. Retroviruses are RNA viruses that contain an RNA genome. The gag, pol, and env genes are flanked by long terminal repeat (LTR) sequences (or their corresponding proteins). The 5′ and 3′ LTR sequences promote transcription and polyadenylation of mRNAs.

The retroviral vector may provide a regulable transactivating element, an internal ribosome reentry site (IRES), a selection marker, and a target heterologous gene operated by a regulable promoter.

Alternatively, multiple sequences may be expressed under the control of multiple promoters. Finally, the retroviral vector may contain cis-acting sequences necessary for reverse transcription and integration. Upon infection, the RNA is reverse transcribed to DNA that integrates efficiently into the host genome. The recombinant retrovirus of this invention is genetically modified in such a way that some of the retroviral, infectious genes of the native virus have been removed and in certain instances replaced instead with a target nucleic acid sequence for genetic modification of the cell. The sequences may be exogenous DNA or RNA, in its natural or altered form.

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Patent 2024
Base Sequence Cells Cloning Vectors Electroporation Gene Editing Genes Genes, env Genes, Viral Genome Infection Internal Ribosome Entry Sites Long Terminal Repeat Polyadenylation Proteins Retroviridae Retroviridae Infections Reverse Transcription Ribosomes RNA, Messenger RNA Viruses Transcription, Genetic

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More about "Reverse Transcription"

Reverse transcription (RT) is a fundamental molecular biology technique that enables the conversion of RNA into complementary DNA (cDNA) using the enzyme reverse transcriptase.
This process is essential for studying gene expression, detecting viral infections, and investigating various biological processes.
The TRIzol reagent and RNeasy Mini Kit are commonly used for RNA extraction, while the High-Capacity cDNA Reverse Transcription Kit, QuantiTect Reverse Transcription Kit, and PrimeScript RT reagent kit are popular options for performing the reverse transcription step.
Once the cDNA is synthesized, it can be further analyzed using real-time PCR (qPCR) techniques, such as the StepOnePlus Real-Time PCR System and SYBR Green PCR Master Mix.
The TaqMan MicroRNA Reverse Transcription Kit is specifically designed for the detection and quantification of microRNAs.
The RNeasy kit is another versatile tool for RNA purification and can be used in combination with reverse transcription and qPCR to study gene expression.
PubCompare.ai's AI-driven platform offers innovative tools to help researchers optimize reverse transcription protocols, locate the best approaches from literature, preprints, and patents, and enhance reproducibility and research accuracy.
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