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Effects of formalin fixation and paraffin embedding on miRNA. A: Frozen sample-derived total <t>RNA</t> electrophorogram on <t>Agilent</t> small RNA chip. B: FFPE-derived total RNA electrophorogram on Agilent small RNA chip.
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1) Product Images from "An Array-Based Analysis of MicroRNA Expression Comparing Matched Frozen and Formalin-Fixed Paraffin-Embedded Human Tissue Samples"

Article Title: An Array-Based Analysis of MicroRNA Expression Comparing Matched Frozen and Formalin-Fixed Paraffin-Embedded Human Tissue Samples

Journal: The Journal of Molecular Diagnostics : JMD

doi: 10.2353/jmoldx.2008.080077

Effects of formalin fixation and paraffin embedding on miRNA. A: Frozen sample-derived total RNA electrophorogram on Agilent small RNA chip. B: FFPE-derived total RNA electrophorogram on Agilent small RNA chip.
Figure Legend Snippet: Effects of formalin fixation and paraffin embedding on miRNA. A: Frozen sample-derived total RNA electrophorogram on Agilent small RNA chip. B: FFPE-derived total RNA electrophorogram on Agilent small RNA chip.

Techniques Used: Derivative Assay, Chromatin Immunoprecipitation, Formalin-fixed Paraffin-Embedded

2) Product Images from "Microarray analysis of RNA extracted from formalin-fixed, paraffin-embedded and matched fresh-frozen ovarian adenocarcinomas"

Article Title: Microarray analysis of RNA extracted from formalin-fixed, paraffin-embedded and matched fresh-frozen ovarian adenocarcinomas

Journal: BMC Medical Genomics

doi: 10.1186/1755-8794-2-23

Bioanalyzer profiles of total RNA (A) and cRNA (B) of matched FF and FFPE ovarian serous adenocarcinoma samples 3136, 3138, 3194, 3207 and 390 . The method used for RNA extraction (Qiagen, Agencourt, Ambion) is indicated for each sample type. The RNA Integrity Number (RIN) is shown next to each total RNA profile.
Figure Legend Snippet: Bioanalyzer profiles of total RNA (A) and cRNA (B) of matched FF and FFPE ovarian serous adenocarcinoma samples 3136, 3138, 3194, 3207 and 390 . The method used for RNA extraction (Qiagen, Agencourt, Ambion) is indicated for each sample type. The RNA Integrity Number (RIN) is shown next to each total RNA profile.

Techniques Used: Formalin-fixed Paraffin-Embedded, RNA Extraction

3) Product Images from "Novel zinc-based fixative for high quality DNA, RNA and protein analysis"

Article Title: Novel zinc-based fixative for high quality DNA, RNA and protein analysis

Journal: Nucleic Acids Research

doi: 10.1093/nar/gkm433

Assessment of mouse liver RNA quality using the Agilent 2100 Bioanalyser. ( a ) Typical graphs showing severely degraded, partially degraded and intact RNA. ( b ) Graphs showing RNA quality from tissues fixed in: NBF, Z2, Z7 and also fresh-frozen mouse liver.
Figure Legend Snippet: Assessment of mouse liver RNA quality using the Agilent 2100 Bioanalyser. ( a ) Typical graphs showing severely degraded, partially degraded and intact RNA. ( b ) Graphs showing RNA quality from tissues fixed in: NBF, Z2, Z7 and also fresh-frozen mouse liver.

Techniques Used:

4) Product Images from "Characterization of Salivary RNA by cDNA Library Analysis"

Article Title: Characterization of Salivary RNA by cDNA Library Analysis

Journal:

doi: 10.1016/j.archoralbio.2006.08.014

Virtual gel derived from Agilent Bioanalyzer Analysis. Shown are electropherograms of RNA extracted from saliva (A) and MCF-7 breast cancer cells (B) before and after treatment with DNase or RNase as described in the materials and methods section. The salivary RNA was concentrated 10x before it was run on a Picochip. The two peaks that were observed in the Agilent profile of saliva are indicated with a * and ** on the right side of the saliva electropherogram. The cell line RNA was run on a Nanochip.
Figure Legend Snippet: Virtual gel derived from Agilent Bioanalyzer Analysis. Shown are electropherograms of RNA extracted from saliva (A) and MCF-7 breast cancer cells (B) before and after treatment with DNase or RNase as described in the materials and methods section. The salivary RNA was concentrated 10x before it was run on a Picochip. The two peaks that were observed in the Agilent profile of saliva are indicated with a * and ** on the right side of the saliva electropherogram. The cell line RNA was run on a Nanochip.

Techniques Used: Derivative Assay

5) Product Images from "Revelation of mRNAs and proteins in porcine milk exosomes by transcriptomic and proteomic analysis"

Article Title: Revelation of mRNAs and proteins in porcine milk exosomes by transcriptomic and proteomic analysis

Journal: BMC Veterinary Research

doi: 10.1186/s12917-017-1021-8

Identification of proteins and mRNAs in porcine milk exosomes. a detection of the exosomal marker proteins CD63 and CD9 by Western blotting. b SDS-PAGE. c RNA sample analyzed by the Agilent Bioanalyzer 2100. d distribution of genen’s coverage
Figure Legend Snippet: Identification of proteins and mRNAs in porcine milk exosomes. a detection of the exosomal marker proteins CD63 and CD9 by Western blotting. b SDS-PAGE. c RNA sample analyzed by the Agilent Bioanalyzer 2100. d distribution of genen’s coverage

Techniques Used: Marker, Western Blot, SDS Page

6) Product Images from "A multidimensional platform for the purification of non-coding RNA species"

Article Title: A multidimensional platform for the purification of non-coding RNA species

Journal: Nucleic Acids Research

doi: 10.1093/nar/gkt668

Separation of CCRF-SB and E. coli total RNA by SE-HPLC. ( A ) Typical profile of E. coli total RNA consisting of 23S, 16S rRNAs and co-eluting 5S rRNA and tRNA obtained on a Bio SEC-5 1000 Å column. ( B ) Typical profile of CCRF-SB total RNA consisting of 28S, 18S rRNAs and co-eluting 5.8S, 5S rRNA and tRNA obtained on a Bio SEC-5 1000 Å column. ( C ) Typical profile of E. coli total RNA consisting of 5S rRNA, tRNAs and co-eluting 16S and 23S rRNAs obtained on a Bio SEC-3 300 Å column. ( D ) Typical profile of CCRF-SB total RNA consisting of 5.8S, 5S rRNA, tRNAs and co-eluting 18S and 28S rRNAs obtained on a Bio SEC-3 300 Å column. The chromatograms show the analysis of 10 µg of total RNA extracted using Trizol reagent (Materials and Methods). ( E ) Separation of miRNA, tRNAs, 5.8S, 5S rRNAs, putative snRNAs and snoRNAs, and co-eluting 18S and 28S rRNAs from human lymphoblastic cell line CCRF-SB total RNA by IP RP HPLC obtained on a SOURCE 5RPC ST 4.5/150 column. The identity and purity of the RNAs collected in each fraction was validated with Bioanalyzer RNA 6000 Pico and Small RNA LabChips ( Supplementary Figures S1 and S3 ).
Figure Legend Snippet: Separation of CCRF-SB and E. coli total RNA by SE-HPLC. ( A ) Typical profile of E. coli total RNA consisting of 23S, 16S rRNAs and co-eluting 5S rRNA and tRNA obtained on a Bio SEC-5 1000 Å column. ( B ) Typical profile of CCRF-SB total RNA consisting of 28S, 18S rRNAs and co-eluting 5.8S, 5S rRNA and tRNA obtained on a Bio SEC-5 1000 Å column. ( C ) Typical profile of E. coli total RNA consisting of 5S rRNA, tRNAs and co-eluting 16S and 23S rRNAs obtained on a Bio SEC-3 300 Å column. ( D ) Typical profile of CCRF-SB total RNA consisting of 5.8S, 5S rRNA, tRNAs and co-eluting 18S and 28S rRNAs obtained on a Bio SEC-3 300 Å column. The chromatograms show the analysis of 10 µg of total RNA extracted using Trizol reagent (Materials and Methods). ( E ) Separation of miRNA, tRNAs, 5.8S, 5S rRNAs, putative snRNAs and snoRNAs, and co-eluting 18S and 28S rRNAs from human lymphoblastic cell line CCRF-SB total RNA by IP RP HPLC obtained on a SOURCE 5RPC ST 4.5/150 column. The identity and purity of the RNAs collected in each fraction was validated with Bioanalyzer RNA 6000 Pico and Small RNA LabChips ( Supplementary Figures S1 and S3 ).

Techniques Used: High Performance Liquid Chromatography, Size-exclusion Chromatography

Isolation of ncRNA from P. berghei -infected rodent reticulocytes. ( A ) Bioanalyzer analysis of total RNA extracted from whole blood from uninfected rats (black line) and total RNA extracted from P. berghei schizonts purified from infected rat erythrocytes following lysis of the red blood cells and washing of the schizonts, as described in Supplementary Methods (gray lane). ( B ) 2D-SEC purification of P. berghei ncRNA. Total RNA from schizonts purified from lysed rodent reticulocytes was resolved on the 2D HPLC system, with Bio SEC-3 300 Å resolution of 5.8S rRNA ( 1 ), 5s rRNA ( 2 ), putative snRNA/snoRNA ( 3 ) and tRNA ( 4 ), and Bio SEC-5 1000 Å resolution of the 28s 800 nt rRNA fragment ( 6 ) from the co-eluting 18s rRNA and 28s 3000 nt rRNA fragment ( 5 ). Individual RNA species were collected from the 2-D HPLC elution, and the purity and identity of each fraction was evaluated by Bioanalyzer analysis as shown in Supplementary Figure S6 .
Figure Legend Snippet: Isolation of ncRNA from P. berghei -infected rodent reticulocytes. ( A ) Bioanalyzer analysis of total RNA extracted from whole blood from uninfected rats (black line) and total RNA extracted from P. berghei schizonts purified from infected rat erythrocytes following lysis of the red blood cells and washing of the schizonts, as described in Supplementary Methods (gray lane). ( B ) 2D-SEC purification of P. berghei ncRNA. Total RNA from schizonts purified from lysed rodent reticulocytes was resolved on the 2D HPLC system, with Bio SEC-3 300 Å resolution of 5.8S rRNA ( 1 ), 5s rRNA ( 2 ), putative snRNA/snoRNA ( 3 ) and tRNA ( 4 ), and Bio SEC-5 1000 Å resolution of the 28s 800 nt rRNA fragment ( 6 ) from the co-eluting 18s rRNA and 28s 3000 nt rRNA fragment ( 5 ). Individual RNA species were collected from the 2-D HPLC elution, and the purity and identity of each fraction was evaluated by Bioanalyzer analysis as shown in Supplementary Figure S6 .

Techniques Used: Isolation, Infection, Purification, Lysis, Size-exclusion Chromatography, High Performance Liquid Chromatography

Fluorometric quantitation of purified RNA using RiboGreen with adjustments for species-specific responses. ( A ) Fluorescence enhancement of RiboGreen on binding to E. coli total RNA (black square) and HPLC purified E. coli 23S rRNA (black circle), 16S rRNA (black diamond) and tRNA (black triangle). ( B ) Fluorescence enhancement of RiboGreen on binding to CCRF-SB total RNA (black square) and HPLC purified CCRF-SB 28S rRNA (black circle), 18S rRNA (black diamond) and tRNA (black triangle). ( C ) RNA concentration curves of E. coli total RNA (black square) and HPLC purified E coli 23S rRNA (black circle), 16S rRNA (black diamond) and tRNA (black triangle). ( D ) RNA concentration curves of CCRF-SB total RNA (black square) and HPLC purified CCRF-SB 28S rRNA (black circle), 18S rRNA (black diamond) and tRNA (black triangle). The fluorescence of each RNA species with concentrations from 0 to 1000 ng/ml stained with RiboGreen was measured for fluorescence at 528/20 nm.
Figure Legend Snippet: Fluorometric quantitation of purified RNA using RiboGreen with adjustments for species-specific responses. ( A ) Fluorescence enhancement of RiboGreen on binding to E. coli total RNA (black square) and HPLC purified E. coli 23S rRNA (black circle), 16S rRNA (black diamond) and tRNA (black triangle). ( B ) Fluorescence enhancement of RiboGreen on binding to CCRF-SB total RNA (black square) and HPLC purified CCRF-SB 28S rRNA (black circle), 18S rRNA (black diamond) and tRNA (black triangle). ( C ) RNA concentration curves of E. coli total RNA (black square) and HPLC purified E coli 23S rRNA (black circle), 16S rRNA (black diamond) and tRNA (black triangle). ( D ) RNA concentration curves of CCRF-SB total RNA (black square) and HPLC purified CCRF-SB 28S rRNA (black circle), 18S rRNA (black diamond) and tRNA (black triangle). The fluorescence of each RNA species with concentrations from 0 to 1000 ng/ml stained with RiboGreen was measured for fluorescence at 528/20 nm.

Techniques Used: Quantitation Assay, Purification, Fluorescence, Binding Assay, High Performance Liquid Chromatography, Concentration Assay, Staining

The 2D-SEC of BCG total RNA preserves the native post-transcriptional ribonucleoside modifications in purified tRNA. ( A ) Baseline separation of BCG total RNA to its component 23S (insert 1), 16S (insert 2), 5S rRNAs (insert 3) and tRNA (insert 4) obtained on a Bio SEC-5 1000 Å (column 1) and Bio SEC-3 300 Å (column 2) two-column online HPLC system (ID 7.8 mm, 300 mm for each column) demonstrating the purity and quality of each RNA species based on sequence lengths on the Bioanalyzer RNA 6000 Pico and Small RNA LabChips. ( B ) Extracted ion chromatograms of naturally occurring modified ribonucleosides in hydrolyzed BCG tRNA identified by HPLC-coupled triple quadrupole mass spectrometry in multiple reaction monitoring mode. The peaks of m 1 A (2.87 min) and m 7 G (4.53 min) are marked with ‘//’ to indicate that they are in different scales from other peaks. Identities of the 18 post-transcriptional modifications detected are shown in Supplementary Table S2 . Inset: MS/MS validation of N 6 ,N 6 -dimethyladenosine ( ). Ribonucleoside with m/z of 296.1356 was targeted for CID fragmentation on a high mass accuracy quadrupole time-of-flight mass spectrometer yielding a daughter ion with m/z 164.0927.
Figure Legend Snippet: The 2D-SEC of BCG total RNA preserves the native post-transcriptional ribonucleoside modifications in purified tRNA. ( A ) Baseline separation of BCG total RNA to its component 23S (insert 1), 16S (insert 2), 5S rRNAs (insert 3) and tRNA (insert 4) obtained on a Bio SEC-5 1000 Å (column 1) and Bio SEC-3 300 Å (column 2) two-column online HPLC system (ID 7.8 mm, 300 mm for each column) demonstrating the purity and quality of each RNA species based on sequence lengths on the Bioanalyzer RNA 6000 Pico and Small RNA LabChips. ( B ) Extracted ion chromatograms of naturally occurring modified ribonucleosides in hydrolyzed BCG tRNA identified by HPLC-coupled triple quadrupole mass spectrometry in multiple reaction monitoring mode. The peaks of m 1 A (2.87 min) and m 7 G (4.53 min) are marked with ‘//’ to indicate that they are in different scales from other peaks. Identities of the 18 post-transcriptional modifications detected are shown in Supplementary Table S2 . Inset: MS/MS validation of N 6 ,N 6 -dimethyladenosine ( ). Ribonucleoside with m/z of 296.1356 was targeted for CID fragmentation on a high mass accuracy quadrupole time-of-flight mass spectrometer yielding a daughter ion with m/z 164.0927.

Techniques Used: Size-exclusion Chromatography, Purification, High Performance Liquid Chromatography, Sequencing, Modification, Mass Spectrometry

7) Product Images from "Noncoding transcription within the Igh distal VH region at PAIR elements affects the 3D structure of the Igh locus in pro-B cells"

Article Title: Noncoding transcription within the Igh distal VH region at PAIR elements affects the 3D structure of the Igh locus in pro-B cells

Journal: Proceedings of the National Academy of Sciences of the United States of America

doi: 10.1073/pnas.1208398109

RNA-seq analysis of the Igh locus. ( A ) RNA-seq was performed on Rag1 −/− pro–B-cell RNA enriched on a custom Agilent array coated with the entire nonrepetitive DNA of the Igh locus. Antisense transcripts throughout the VH region of Igh locus are shown. ( B ) Mapping of antisense transcription in distal half of the VH J558 region. The relative position of all 14 PAIR elements is shown.
Figure Legend Snippet: RNA-seq analysis of the Igh locus. ( A ) RNA-seq was performed on Rag1 −/− pro–B-cell RNA enriched on a custom Agilent array coated with the entire nonrepetitive DNA of the Igh locus. Antisense transcripts throughout the VH region of Igh locus are shown. ( B ) Mapping of antisense transcription in distal half of the VH J558 region. The relative position of all 14 PAIR elements is shown.

Techniques Used: RNA Sequencing Assay

8) Product Images from "Modified CTAB and TRIzol protocols improve RNA extraction from chemically complex Embryophyta"

Article Title: Modified CTAB and TRIzol protocols improve RNA extraction from chemically complex Embryophyta

Journal: Applications in Plant Sciences

doi: 10.3732/apps.1400105

Examples of Agilent 2100 Bioanalyzer spectra of total RNA showing improvement with Options 1 and 2 compared to Option 3. Each graph shows the intensity of the peaks of the ribosomal RNA subunits: nuclear large-28S, small-18S, cytoplasmic, mitochondrial, and chloroplastic (smaller subunits). The electrophoretic gel for each sample is shown to the right indicating the subunit bands or degradation (i.e., smear). nt = number of estimated nucleotides based on ladder; FU = fluorescence unit (i.e., intensity of peak). (A) Degraded ribosomal RNA subunits of Canella winterana (L.) Gaertn. extracted with Option 3 that resulted in an estimation of 27 μg of RNA, but the subunits are degraded. (B) A second example using Option 3, Muntingia calabura L., also shows an inflated quantity reading with degraded subunits. (C) Canella winterana , extracted with Option 1, indicating peaks for intact ribosomal RNA subunits. (D) Muntingia calabura extracted with Option 2.
Figure Legend Snippet: Examples of Agilent 2100 Bioanalyzer spectra of total RNA showing improvement with Options 1 and 2 compared to Option 3. Each graph shows the intensity of the peaks of the ribosomal RNA subunits: nuclear large-28S, small-18S, cytoplasmic, mitochondrial, and chloroplastic (smaller subunits). The electrophoretic gel for each sample is shown to the right indicating the subunit bands or degradation (i.e., smear). nt = number of estimated nucleotides based on ladder; FU = fluorescence unit (i.e., intensity of peak). (A) Degraded ribosomal RNA subunits of Canella winterana (L.) Gaertn. extracted with Option 3 that resulted in an estimation of 27 μg of RNA, but the subunits are degraded. (B) A second example using Option 3, Muntingia calabura L., also shows an inflated quantity reading with degraded subunits. (C) Canella winterana , extracted with Option 1, indicating peaks for intact ribosomal RNA subunits. (D) Muntingia calabura extracted with Option 2.

Techniques Used: Fluorescence

9) Product Images from "Data on differentially expressed miRNAs in dogs infected with Leishmania infantum"

Article Title: Data on differentially expressed miRNAs in dogs infected with Leishmania infantum

Journal: Data in Brief

doi: 10.1016/j.dib.2018.01.007

Quality of miRNA. Bioanalyzer gel image of RNA samples used for microarray analysis. L (Ladder) Each number represents the sample of one animal. RNA Integrity Number (RIN) is respectively 9.1 (1), 10(2), 10 (3), 9.7 (4), 10(5), 8.8(6) and 9.4(7) in the seven samples illustrated.
Figure Legend Snippet: Quality of miRNA. Bioanalyzer gel image of RNA samples used for microarray analysis. L (Ladder) Each number represents the sample of one animal. RNA Integrity Number (RIN) is respectively 9.1 (1), 10(2), 10 (3), 9.7 (4), 10(5), 8.8(6) and 9.4(7) in the seven samples illustrated.

Techniques Used: Microarray

10) Product Images from "Novel zinc-based fixative for high quality DNA, RNA and protein analysis"

Article Title: Novel zinc-based fixative for high quality DNA, RNA and protein analysis

Journal: Nucleic Acids Research

doi: 10.1093/nar/gkm433

Assessment of mouse liver RNA quality using the Agilent 2100 Bioanalyser. ( a ) Typical graphs showing severely degraded, partially degraded and intact RNA. ( b ) Graphs showing RNA quality from tissues fixed in: NBF, Z2, Z7 and also fresh-frozen mouse liver.
Figure Legend Snippet: Assessment of mouse liver RNA quality using the Agilent 2100 Bioanalyser. ( a ) Typical graphs showing severely degraded, partially degraded and intact RNA. ( b ) Graphs showing RNA quality from tissues fixed in: NBF, Z2, Z7 and also fresh-frozen mouse liver.

Techniques Used:

11) Product Images from "miR-202 acts as a potential tumor suppressor in breast cancer"

Article Title: miR-202 acts as a potential tumor suppressor in breast cancer

Journal:

doi: 10.3892/ol.2018.8726

miR-202 inhibits the expression of KRAS in breast cells. (A) Correlation analysis between miR-202 and KRAS expression. The correlation formula is y=−0.4345×+0.8545. (B) The mirDB tool predicted that miR-202 may target KRAS. (C) A luciferase reporter gene assay confirmed that miR-202 was able to target KRAS. (D) The protein and (E) mRNA expression in KRAS was measured in MCF7 cells treated with an miR-202 mimic using western blot and RT-qPCR, respectively. (F) The protein and (G) mRNA expression in KRAS was measured in MCF7 cells treated with an miR-202 inhibitor using western blot and RT-qPCR, respectively. GAPDH was used as an internal loading control. Each bar represents the mean ± standard deviation of three independent experiments; **P < 0.05 vs. the control. miR, micro RNA; RT-qPCR, reverse transcription-quantitative polymerase chain reaction.
Figure Legend Snippet: miR-202 inhibits the expression of KRAS in breast cells. (A) Correlation analysis between miR-202 and KRAS expression. The correlation formula is y=−0.4345×+0.8545. (B) The mirDB tool predicted that miR-202 may target KRAS. (C) A luciferase reporter gene assay confirmed that miR-202 was able to target KRAS. (D) The protein and (E) mRNA expression in KRAS was measured in MCF7 cells treated with an miR-202 mimic using western blot and RT-qPCR, respectively. (F) The protein and (G) mRNA expression in KRAS was measured in MCF7 cells treated with an miR-202 inhibitor using western blot and RT-qPCR, respectively. GAPDH was used as an internal loading control. Each bar represents the mean ± standard deviation of three independent experiments; **P < 0.05 vs. the control. miR, micro RNA; RT-qPCR, reverse transcription-quantitative polymerase chain reaction.

Techniques Used: Expressing, Luciferase, Reporter Gene Assay, Western Blot, Quantitative RT-PCR, Standard Deviation, Real-time Polymerase Chain Reaction

The expression of miR-202 and KRAS in breast cancer. (A) Relative miR-202 expression in 30 pairs of breast cancer tissues and adjacent normal counterpart tissues was detected using real-time PCR. (B) Relative miR-202 expression in 293, MCF7 and MDA-MB-231 cell lines. (C) Relative KRAS expression in 30 pairs of breast cancer tissues and adjacent normal counterpart tissues was detected using real-time PCR. (D) Relative KRAS expression in 293, MCF7 and MDA-MB-231 cell lines. *P < 0.05 and **P < 0.01 vs. 293 cells or adjacent normal tissue. miR, micro RNA; PCR, polymerase chain reaction.
Figure Legend Snippet: The expression of miR-202 and KRAS in breast cancer. (A) Relative miR-202 expression in 30 pairs of breast cancer tissues and adjacent normal counterpart tissues was detected using real-time PCR. (B) Relative miR-202 expression in 293, MCF7 and MDA-MB-231 cell lines. (C) Relative KRAS expression in 30 pairs of breast cancer tissues and adjacent normal counterpart tissues was detected using real-time PCR. (D) Relative KRAS expression in 293, MCF7 and MDA-MB-231 cell lines. *P < 0.05 and **P < 0.01 vs. 293 cells or adjacent normal tissue. miR, micro RNA; PCR, polymerase chain reaction.

Techniques Used: Expressing, Real-time Polymerase Chain Reaction, Multiple Displacement Amplification, Polymerase Chain Reaction

12) Product Images from "Studies on Xenopus laevis intestine reveal biological pathways underlying vertebrate gut adaptation from embryo to adult"

Article Title: Studies on Xenopus laevis intestine reveal biological pathways underlying vertebrate gut adaptation from embryo to adult

Journal: Genome Biology

doi: 10.1186/gb-2010-11-5-r55

Gene expression during mouse development . RT-qPCR analysis was carried out for the indicated genes on mouse intestinal RNA at indicated stages. Note that the expression patterns of mouse EB13 , FCNA , MMP11 , MMP14 , PPP1RA1 and SLC7A2 were similar to those of their homologs in Xenopus during metamorphosis as observed by microarray, that is, there were higher levels of expression shortly after birth in the mouse when T3 levels are high, just like at metamorphic climax. The expression of NPL and RENBP represent profiles of genes that differ from those in Xenopus . All RT-qPCR results are expressed relative to the control RPS13 , with the expression of the genes at E17 arbitrarily set to 1.
Figure Legend Snippet: Gene expression during mouse development . RT-qPCR analysis was carried out for the indicated genes on mouse intestinal RNA at indicated stages. Note that the expression patterns of mouse EB13 , FCNA , MMP11 , MMP14 , PPP1RA1 and SLC7A2 were similar to those of their homologs in Xenopus during metamorphosis as observed by microarray, that is, there were higher levels of expression shortly after birth in the mouse when T3 levels are high, just like at metamorphic climax. The expression of NPL and RENBP represent profiles of genes that differ from those in Xenopus . All RT-qPCR results are expressed relative to the control RPS13 , with the expression of the genes at E17 arbitrarily set to 1.

Techniques Used: Expressing, Quantitative RT-PCR, Microarray

13) Product Images from "Gene expression analysis on small numbers of invasive cells collected by chemotaxis from primary mammary tumors of the mouse"

Article Title: Gene expression analysis on small numbers of invasive cells collected by chemotaxis from primary mammary tumors of the mouse

Journal: BMC Biotechnology

doi: 10.1186/1472-6750-3-13

The RNA from 200 and 400 cells is of equal amount and quality of RNA purified by conventional methods. Figure 5A : Total RNA isolated from microneedle collected cells was checked using Agilent Bioanalyzer and RNA 6000 Pico kit. The size distribution and rRNA ratio (28S/18S = 2.7) indicates good intactness of RNA sample. Figure 5B : A standard curve was generated for the CT value of a known quantity of RNA from a specific cell number using the β-actin primers for real-time PCR. The RNA from 200 and 400 cells were amplified by the SMART PCR method and run identically by real-time PCR. The CT values for the amplified RNA fall on the curve showing that the appropriate amount of the house keeping gene is present in the amplified sample. The CT values for the amplified samples are designated by the red asterisks.
Figure Legend Snippet: The RNA from 200 and 400 cells is of equal amount and quality of RNA purified by conventional methods. Figure 5A : Total RNA isolated from microneedle collected cells was checked using Agilent Bioanalyzer and RNA 6000 Pico kit. The size distribution and rRNA ratio (28S/18S = 2.7) indicates good intactness of RNA sample. Figure 5B : A standard curve was generated for the CT value of a known quantity of RNA from a specific cell number using the β-actin primers for real-time PCR. The RNA from 200 and 400 cells were amplified by the SMART PCR method and run identically by real-time PCR. The CT values for the amplified RNA fall on the curve showing that the appropriate amount of the house keeping gene is present in the amplified sample. The CT values for the amplified samples are designated by the red asterisks.

Techniques Used: Purification, Isolation, Generated, Real-time Polymerase Chain Reaction, Amplification, Polymerase Chain Reaction

14) Product Images from "The stage-specific testicular germ cell apoptotic response to low dose X-irradiation and 2,5-hexanedione combined exposure. I. Validation of the laser capture microdissection method for qRT-PCR array application"

Article Title: The stage-specific testicular germ cell apoptotic response to low dose X-irradiation and 2,5-hexanedione combined exposure. I. Validation of the laser capture microdissection method for qRT-PCR array application

Journal:

doi: 10.1177/0192623314526319

LCM-derived seminiferous tubule RNA quality assessment. Digital gel (A) and electropherogram results (B–C) obtained with the Agilent 2100 Bioanalyzer. Electropherogram results are shown for before (B) and after (C) DNase treatment and RNA concentration,
Figure Legend Snippet: LCM-derived seminiferous tubule RNA quality assessment. Digital gel (A) and electropherogram results (B–C) obtained with the Agilent 2100 Bioanalyzer. Electropherogram results are shown for before (B) and after (C) DNase treatment and RNA concentration,

Techniques Used: Laser Capture Microdissection, Derivative Assay, Concentration Assay

15) Product Images from "Assessment of the relationship between pre-chip and post-chip quality measures for Affymetrix GeneChip expression data"

Article Title: Assessment of the relationship between pre-chip and post-chip quality measures for Affymetrix GeneChip expression data

Journal: BMC Bioinformatics

doi: 10.1186/1471-2105-7-211

Total RNA Gel images from the Bioanalyser (Agilent) . Representative total RNA samples of varying quality, as assessed objectively by RIN and by subjective assessment. Selected corresponding pre- and post-chip variable assessments are also shown. Samples identified as outliers on post-chip quality control measures but not excluded are labelled (*); outliers excluded from expression analysis are labelled (**). Sample from case with prolonged agonal state (†). Sample not run on arrays due to poor quality total RNA (‡). n.d. is value not determined. CB, cerebellum; CN, caudate nucleus; MC, motor cortex.
Figure Legend Snippet: Total RNA Gel images from the Bioanalyser (Agilent) . Representative total RNA samples of varying quality, as assessed objectively by RIN and by subjective assessment. Selected corresponding pre- and post-chip variable assessments are also shown. Samples identified as outliers on post-chip quality control measures but not excluded are labelled (*); outliers excluded from expression analysis are labelled (**). Sample from case with prolonged agonal state (†). Sample not run on arrays due to poor quality total RNA (‡). n.d. is value not determined. CB, cerebellum; CN, caudate nucleus; MC, motor cortex.

Techniques Used: Chromatin Immunoprecipitation, Expressing

16) Product Images from "Tau protein liquid–liquid phase separation can initiate tau aggregation"

Article Title: Tau protein liquid–liquid phase separation can initiate tau aggregation

Journal: The EMBO Journal

doi: 10.15252/embj.201798049

Factors inducing tau aggregation also lead to tau LLPS Aggregation co‐factors heparin and RNA induce p‐tau441 droplet formation in absence of crowding agent PEG. FTD mutations (∆K280, P301L, P301S, A152T; green circles), which trigger tau oligomerization and aggregation, can induce tau droplets (white arrows) in tau441 in absence of phosphorylation (2 μM protein, 10% PEG). In contrast, the anti‐aggregation mutant ∆K280/PP (black circle), in which two proline insertions in R2 and R3 prohibit tau repeat domain aggregation, fails to trigger tau441 LLPS. Progressive aggregate formation from tauP301L droplets. Droplets of non‐phosphorylated FTD‐mutant tauP301L show progressive aggregate formation when incubated at room temperature; clusters of tau protein aggregates connect individual droplets after 72 h, which increased at 96 h. ThioS fluorescence in tauP301L droplets increased over time maybe due to viscosity increase, with less droplets but more ThioS‐positive aggregates in the preparation after 96 h. Tau (TauHMW, black asterisk in Western blot) isolated from the high molecular weight (HMW) protein fraction of Alzheimer's disease brain extract by affinity chromatography (anti‐human tau antibody HT7) initiates tau aggregation (white arrowheads) in HEK TauRDP301S‐CFP/YFP cells. In the presence of molecular crowding (10% PEG), droplets and large aggregates can be observed in TauHMW preparations after 1–2 min.
Figure Legend Snippet: Factors inducing tau aggregation also lead to tau LLPS Aggregation co‐factors heparin and RNA induce p‐tau441 droplet formation in absence of crowding agent PEG. FTD mutations (∆K280, P301L, P301S, A152T; green circles), which trigger tau oligomerization and aggregation, can induce tau droplets (white arrows) in tau441 in absence of phosphorylation (2 μM protein, 10% PEG). In contrast, the anti‐aggregation mutant ∆K280/PP (black circle), in which two proline insertions in R2 and R3 prohibit tau repeat domain aggregation, fails to trigger tau441 LLPS. Progressive aggregate formation from tauP301L droplets. Droplets of non‐phosphorylated FTD‐mutant tauP301L show progressive aggregate formation when incubated at room temperature; clusters of tau protein aggregates connect individual droplets after 72 h, which increased at 96 h. ThioS fluorescence in tauP301L droplets increased over time maybe due to viscosity increase, with less droplets but more ThioS‐positive aggregates in the preparation after 96 h. Tau (TauHMW, black asterisk in Western blot) isolated from the high molecular weight (HMW) protein fraction of Alzheimer's disease brain extract by affinity chromatography (anti‐human tau antibody HT7) initiates tau aggregation (white arrowheads) in HEK TauRDP301S‐CFP/YFP cells. In the presence of molecular crowding (10% PEG), droplets and large aggregates can be observed in TauHMW preparations after 1–2 min.

Techniques Used: Mutagenesis, Incubation, Fluorescence, Western Blot, Isolation, Molecular Weight, Affinity Chromatography

17) Product Images from "Human saliva, plasma and breast milk exosomes contain RNA: uptake by macrophages"

Article Title: Human saliva, plasma and breast milk exosomes contain RNA: uptake by macrophages

Journal: Journal of Translational Medicine

doi: 10.1186/1479-5876-9-9

Detection of mRNA in plasma exosomes using a Bioanalyzer. The exosomal RNA was transcribed to cDNA using an oligo (dT) primer. The results show that a portion of the RNA in plasma exosomes is mRNA. Arrows show the peaks for the lower and upper markers. The peaks in between these markers indicate the presence of cDNA synthesised from plasma exosomal RNA.
Figure Legend Snippet: Detection of mRNA in plasma exosomes using a Bioanalyzer. The exosomal RNA was transcribed to cDNA using an oligo (dT) primer. The results show that a portion of the RNA in plasma exosomes is mRNA. Arrows show the peaks for the lower and upper markers. The peaks in between these markers indicate the presence of cDNA synthesised from plasma exosomal RNA.

Techniques Used:

Exosomal RNA analysed using a Bioanalyzer. Total RNA was isolated from saliva, plasma and breast milk exosomes using Trizol ® and analysed with a Bioanalyzer. The results show that exosomes from human saliva, plasma and breast milk contain a dissimilar RNA content compared to cellular RNA from HMC-1 cells, as exosomes contain little or no ribosomal RNA.
Figure Legend Snippet: Exosomal RNA analysed using a Bioanalyzer. Total RNA was isolated from saliva, plasma and breast milk exosomes using Trizol ® and analysed with a Bioanalyzer. The results show that exosomes from human saliva, plasma and breast milk contain a dissimilar RNA content compared to cellular RNA from HMC-1 cells, as exosomes contain little or no ribosomal RNA.

Techniques Used: Isolation

18) Product Images from "Urinary extracellular vesicles for RNA extraction: optimization of a protocol devoid of prokaryote contamination"

Article Title: Urinary extracellular vesicles for RNA extraction: optimization of a protocol devoid of prokaryote contamination

Journal: Journal of Extracellular Vesicles

doi: 10.3402/jev.v5.30281

Pico 6000 RNA Chip electropherograms run in Agilent 2100 Bioanalyzer for RNA samples coming from UEVs extracted with different methods: (a) FastRNA; (b) Qiagen; (c) TRIzol; (d) Norgen; (e) Nucleo-Spin; (f) Quick RNA; (g) mirVana; nt – nucleotide size, grey arrow – marker peak, FU – fluorescence units.
Figure Legend Snippet: Pico 6000 RNA Chip electropherograms run in Agilent 2100 Bioanalyzer for RNA samples coming from UEVs extracted with different methods: (a) FastRNA; (b) Qiagen; (c) TRIzol; (d) Norgen; (e) Nucleo-Spin; (f) Quick RNA; (g) mirVana; nt – nucleotide size, grey arrow – marker peak, FU – fluorescence units.

Techniques Used: Chromatin Immunoprecipitation, Marker, Fluorescence

Profiles of isolated RNA analyzed by Agilent 2100 Bioanalyzer in PicoChip (electropherograms). (a) UEVs RNA enriched via HFD and isolated with Norgen Kit; (b) cellular RNA extracted with FastRNA Kit; (c) UEVs with spike-in of cellular RNA; (d) cellular RNA re-extracted with Norgen Kit; (e) UEVs RNA, cellular RNA and UEVs+cellular RNA electropherograms merged together according to nucleotide size axis; (f) bacterial RNA; (g) cellular RNA and bacterial RNA mixed and run together; (h) cellular RNA and bacterial RNA electropherograms merged together according to nucleotide size axis. Grey arrow – marker dye; blue arrow – UEVs rRNA; red arrow – 18s and 28s rRNA; black arrow – 16s and 23s rRNA.
Figure Legend Snippet: Profiles of isolated RNA analyzed by Agilent 2100 Bioanalyzer in PicoChip (electropherograms). (a) UEVs RNA enriched via HFD and isolated with Norgen Kit; (b) cellular RNA extracted with FastRNA Kit; (c) UEVs with spike-in of cellular RNA; (d) cellular RNA re-extracted with Norgen Kit; (e) UEVs RNA, cellular RNA and UEVs+cellular RNA electropherograms merged together according to nucleotide size axis; (f) bacterial RNA; (g) cellular RNA and bacterial RNA mixed and run together; (h) cellular RNA and bacterial RNA electropherograms merged together according to nucleotide size axis. Grey arrow – marker dye; blue arrow – UEVs rRNA; red arrow – 18s and 28s rRNA; black arrow – 16s and 23s rRNA.

Techniques Used: Isolation, Marker

Small RNA Chip electropherograms run in Agilent 2100 Bioanalyzer for RNA samples coming from UEVs extracted with different methods: (a) FastRNA; (b) Qiagen; (c) TRIzol; (d) Norgen; (e) Nucleo-Spin; (f) Quick RNA; (g) mirVana; nt – nucleotide size, grey arrow – marker peak, FU – fluorescence units.
Figure Legend Snippet: Small RNA Chip electropherograms run in Agilent 2100 Bioanalyzer for RNA samples coming from UEVs extracted with different methods: (a) FastRNA; (b) Qiagen; (c) TRIzol; (d) Norgen; (e) Nucleo-Spin; (f) Quick RNA; (g) mirVana; nt – nucleotide size, grey arrow – marker peak, FU – fluorescence units.

Techniques Used: Chromatin Immunoprecipitation, Marker, Fluorescence

19) Product Images from "Usefulness of miRNA profiles for predicting pathological responses to neoadjuvant chemotherapy in patients with human epidermal growth factor receptor 2-positive breast cancer"

Article Title: Usefulness of miRNA profiles for predicting pathological responses to neoadjuvant chemotherapy in patients with human epidermal growth factor receptor 2-positive breast cancer

Journal:

doi: 10.3892/ol.2017.5628

Example of electrophoretic RNA measurement recorded with an Agilent 2100 bioanalyzer. The electropherogram represents the size of distribution in nt and FU. Peak of RNA fragments was located at ~100 nt in length.RNA integrity number of this sample was
Figure Legend Snippet: Example of electrophoretic RNA measurement recorded with an Agilent 2100 bioanalyzer. The electropherogram represents the size of distribution in nt and FU. Peak of RNA fragments was located at ~100 nt in length.RNA integrity number of this sample was

Techniques Used:

20) Product Images from "Global Analysis of H3K4 Methylation Defines MLL Family Member Targets and Points to a Role for MLL1-Mediated H3K4 Methylation in the Regulation of Transcriptional Initiation by RNA Polymerase II"

Article Title: Global Analysis of H3K4 Methylation Defines MLL Family Member Targets and Points to a Role for MLL1-Mediated H3K4 Methylation in the Regulation of Transcriptional Initiation by RNA Polymerase II

Journal:

doi: 10.1128/MCB.00924-09

H3K4 methylation is broadly lost at some coding and intergenic regions of Hox genes in the absence of Mll1 . H3K4me3, H3K4me2, RNA Pol II, and total H3 profiles were determined across the Hoxa , Hoxb , and Hoxd loci by using a custom Agilent tiling array
Figure Legend Snippet: H3K4 methylation is broadly lost at some coding and intergenic regions of Hox genes in the absence of Mll1 . H3K4me3, H3K4me2, RNA Pol II, and total H3 profiles were determined across the Hoxa , Hoxb , and Hoxd loci by using a custom Agilent tiling array

Techniques Used: Methylation

Related Articles

Reverse Transcription Polymerase Chain Reaction:

Article Title: Novel zinc-based fixative for high quality DNA, RNA and protein analysis
Article Snippet: The effects of 25 different fixative recipes on the fixed quality of tissues from C57BL/6 mice were investigated. .. Results from IHC, PCR, RT–PCR, RNA Agilent Bioanalyser and Real-Time PCR showed that a novel zinc-based fixative (Z7) containing zinc trifluoroacetate, zinc chloride and calcium acetate was significantly better than the standard zinc-based fixative (Z2) and neutral buffered formalin (NBF) for DNA, RNA and protein preservation. .. DNA sequences up to 2.4 kb in length and RNA fragments up to 361 bp in length were successfully amplified from Z7 fixed tissues, as demonstrated by PCR, RT–PCR and Real-Time PCR.

Quantitative RT-PCR:

Article Title: ROCK signalling induced gene expression changes in mouse pancreatic ductal adenocarcinoma cells
Article Snippet: RNA quality was confirmed using the Agilent RNA ScreenTape assay and the Agilent 2200 TapeStation system, which revealed RNA integrity number equivalent (RINe ) values of 10 for all samples. .. Following RNA-seq, principal component analysis indicated that GFP:ER samples that had been treated with EtOH vehicle or 4HT clustered together while ROCK1:ER and ROCK2:ER samples treated with 4HT clustered together separate from the GFP:ER grouping , consistent with the conditional activation of ROCK catalytic activity observed by western blotting ( ).

Article Title: Mechanisms that Determine the Differential Stability of Stx+ and Stx− Lysogens
Article Snippet: Paragraph title: 4.7. qRT-PCR ... RNA was re-suspended in DNaseI buffer and RiboGuard, and residual genomic DNA was removed by treatment with RNase-free DNaseI (Epicentre, Madison, WI, USA) for one hour at 37 °C. cDNA synthesis reactions containing purified RNA, Affinityscript buffer, forward primer, and Affinityscript reverse transcriptase/RNase Block enzyme mix (Agilent Technologies, Cedarville, TX, USA) were incubated at 25 °C for five minutes to allow primer annealing, 45 °C for 45 min for cDNA synthesis, and finally at 95 °C for five minutes to heat kill the reverse transcriptase.

Real-time Polymerase Chain Reaction:

Article Title: Novel zinc-based fixative for high quality DNA, RNA and protein analysis
Article Snippet: The effects of 25 different fixative recipes on the fixed quality of tissues from C57BL/6 mice were investigated. .. Results from IHC, PCR, RT–PCR, RNA Agilent Bioanalyser and Real-Time PCR showed that a novel zinc-based fixative (Z7) containing zinc trifluoroacetate, zinc chloride and calcium acetate was significantly better than the standard zinc-based fixative (Z2) and neutral buffered formalin (NBF) for DNA, RNA and protein preservation. .. DNA sequences up to 2.4 kb in length and RNA fragments up to 361 bp in length were successfully amplified from Z7 fixed tissues, as demonstrated by PCR, RT–PCR and Real-Time PCR.

Article Title: Mechanisms that Determine the Differential Stability of Stx+ and Stx− Lysogens
Article Snippet: RNA was re-suspended in DNaseI buffer and RiboGuard, and residual genomic DNA was removed by treatment with RNase-free DNaseI (Epicentre, Madison, WI, USA) for one hour at 37 °C. cDNA synthesis reactions containing purified RNA, Affinityscript buffer, forward primer, and Affinityscript reverse transcriptase/RNase Block enzyme mix (Agilent Technologies, Cedarville, TX, USA) were incubated at 25 °C for five minutes to allow primer annealing, 45 °C for 45 min for cDNA synthesis, and finally at 95 °C for five minutes to heat kill the reverse transcriptase. .. RNA was re-suspended in DNaseI buffer and RiboGuard, and residual genomic DNA was removed by treatment with RNase-free DNaseI (Epicentre, Madison, WI, USA) for one hour at 37 °C. cDNA synthesis reactions containing purified RNA, Affinityscript buffer, forward primer, and Affinityscript reverse transcriptase/RNase Block enzyme mix (Agilent Technologies, Cedarville, TX, USA) were incubated at 25 °C for five minutes to allow primer annealing, 45 °C for 45 min for cDNA synthesis, and finally at 95 °C for five minutes to heat kill the reverse transcriptase.

Incubation:

Article Title: Mechanisms that Determine the Differential Stability of Stx+ and Stx− Lysogens
Article Snippet: RNA was further purified by acid phenol extraction followed by chloroform: isoamyl alcohol extraction and precipitation. .. RNA was re-suspended in DNaseI buffer and RiboGuard, and residual genomic DNA was removed by treatment with RNase-free DNaseI (Epicentre, Madison, WI, USA) for one hour at 37 °C. cDNA synthesis reactions containing purified RNA, Affinityscript buffer, forward primer, and Affinityscript reverse transcriptase/RNase Block enzyme mix (Agilent Technologies, Cedarville, TX, USA) were incubated at 25 °C for five minutes to allow primer annealing, 45 °C for 45 min for cDNA synthesis, and finally at 95 °C for five minutes to heat kill the reverse transcriptase. .. Quantitation of RNA was performed by real-time PCR.

Expressing:

Article Title: ROCK signalling induced gene expression changes in mouse pancreatic ductal adenocarcinoma cells
Article Snippet: RNA quality was confirmed using the Agilent RNA ScreenTape assay and the Agilent 2200 TapeStation system, which revealed RNA integrity number equivalent (RINe ) values of 10 for all samples. .. Following RNA-seq, principal component analysis indicated that GFP:ER samples that had been treated with EtOH vehicle or 4HT clustered together while ROCK1:ER and ROCK2:ER samples treated with 4HT clustered together separate from the GFP:ER grouping , consistent with the conditional activation of ROCK catalytic activity observed by western blotting ( ).

Genome Wide:

Article Title: Noncoding transcription within the Igh distal VH region at PAIR elements affects the 3D structure of the Igh locus in pro-B cells
Article Snippet: Noncoding germ-line transcription from unrearranged VH genes and intergenic regions of the Igh locus have been well documented ( , ); however, no detailed genome-wide study has been done to quantitate and map all of the sense and antisense germ-line transcripts in the Igh locus. .. Therefore, we subsequently performed a pre-enrichment of RNA on custom Agilent arrays coated with all of the nonrepetitive DNA from the Igh locus, and ran a second RNA-seq experiment with this enriched RNA sample.

Immunohistochemistry:

Article Title: Novel zinc-based fixative for high quality DNA, RNA and protein analysis
Article Snippet: The effects of 25 different fixative recipes on the fixed quality of tissues from C57BL/6 mice were investigated. .. Results from IHC, PCR, RT–PCR, RNA Agilent Bioanalyser and Real-Time PCR showed that a novel zinc-based fixative (Z7) containing zinc trifluoroacetate, zinc chloride and calcium acetate was significantly better than the standard zinc-based fixative (Z2) and neutral buffered formalin (NBF) for DNA, RNA and protein preservation. .. DNA sequences up to 2.4 kb in length and RNA fragments up to 361 bp in length were successfully amplified from Z7 fixed tissues, as demonstrated by PCR, RT–PCR and Real-Time PCR.

Activation Assay:

Article Title: ROCK signalling induced gene expression changes in mouse pancreatic ductal adenocarcinoma cells
Article Snippet: RNA quality was confirmed using the Agilent RNA ScreenTape assay and the Agilent 2200 TapeStation system, which revealed RNA integrity number equivalent (RINe ) values of 10 for all samples. .. Following RNA-seq, principal component analysis indicated that GFP:ER samples that had been treated with EtOH vehicle or 4HT clustered together while ROCK1:ER and ROCK2:ER samples treated with 4HT clustered together separate from the GFP:ER grouping , consistent with the conditional activation of ROCK catalytic activity observed by western blotting ( ).

Sequencing:

Article Title: ROCK signalling induced gene expression changes in mouse pancreatic ductal adenocarcinoma cells
Article Snippet: RNA quality was confirmed using the Agilent RNA ScreenTape assay and the Agilent 2200 TapeStation system, which revealed RNA integrity number equivalent (RINe ) values of 10 for all samples. .. Quantitative reverse transcription PCR (RT-qPCR) analyses validated differences in gene expression upon ROCK1:ER or ROCK2:ER activation identified by RNA seq, including increased Protaglandin-endoperoxidase 2 (Ptgs2 ) RNA ( ) and decreased Trefoil factor 3 (Tff3 ) RNA ( ).

Binding Assay:

Article Title: Noncoding transcription within the Igh distal VH region at PAIR elements affects the 3D structure of the Igh locus in pro-B cells
Article Snippet: Therefore, we subsequently performed a pre-enrichment of RNA on custom Agilent arrays coated with all of the nonrepetitive DNA from the Igh locus, and ran a second RNA-seq experiment with this enriched RNA sample. .. Therefore, we subsequently performed a pre-enrichment of RNA on custom Agilent arrays coated with all of the nonrepetitive DNA from the Igh locus, and ran a second RNA-seq experiment with this enriched RNA sample.

Nucleic Acid Electrophoresis:

Article Title: Novel zinc-based fixative for high quality DNA, RNA and protein analysis
Article Snippet: Results from IHC, PCR, RT–PCR, RNA Agilent Bioanalyser and Real-Time PCR showed that a novel zinc-based fixative (Z7) containing zinc trifluoroacetate, zinc chloride and calcium acetate was significantly better than the standard zinc-based fixative (Z2) and neutral buffered formalin (NBF) for DNA, RNA and protein preservation. .. DNA sequences up to 2.4 kb in length and RNA fragments up to 361 bp in length were successfully amplified from Z7 fixed tissues, as demonstrated by PCR, RT–PCR and Real-Time PCR.

RNA Sequencing Assay:

Article Title: Noncoding transcription within the Igh distal VH region at PAIR elements affects the 3D structure of the Igh locus in pro-B cells
Article Snippet: The number of reads from the first run clearly showed all of the major noncoding transcripts, but was not high enough to allow analysis of weak transcript levels ( ). .. Therefore, we subsequently performed a pre-enrichment of RNA on custom Agilent arrays coated with all of the nonrepetitive DNA from the Igh locus, and ran a second RNA-seq experiment with this enriched RNA sample. .. This approach provided many more reads for the weaker VH sense transcripts ( ).

Article Title: ROCK signalling induced gene expression changes in mouse pancreatic ductal adenocarcinoma cells
Article Snippet: Paragraph title: Quality control of RNA-Seq data ... RNA quality was confirmed using the Agilent RNA ScreenTape assay and the Agilent 2200 TapeStation system, which revealed RNA integrity number equivalent (RINe ) values of 10 for all samples.

Multiple Displacement Amplification:

Article Title: Transcriptomic profiling of human breast and melanoma cells selected by migration through narrow constraints
Article Snippet: The quality of extracted RNA (RNA integrity number equivalent; RINe) of all samples was determined using the Agilent RNA ScreenTape assay and the Agilent 2,200 TapeStation system ( ). .. Following RNA-seq, correlation coefficients were calculated for all pairwise comparisons of biological replicates , which were ≥0.9874292 for MDA-MB-231 cells and ≥0.9995527 for MDA-MB-435 cells.

Isolation:

Article Title: Noncoding transcription within the Igh distal VH region at PAIR elements affects the 3D structure of the Igh locus in pro-B cells
Article Snippet: Therefore, we performed directional RNA-seq that can identify transcripts in both sense and antisense orientations using RNA from freshly isolated Rag1 −/− pro-B cells. .. Therefore, we subsequently performed a pre-enrichment of RNA on custom Agilent arrays coated with all of the nonrepetitive DNA from the Igh locus, and ran a second RNA-seq experiment with this enriched RNA sample.

Purification:

Article Title: Mechanisms that Determine the Differential Stability of Stx+ and Stx− Lysogens
Article Snippet: RNA was further purified by acid phenol extraction followed by chloroform: isoamyl alcohol extraction and precipitation. .. RNA was re-suspended in DNaseI buffer and RiboGuard, and residual genomic DNA was removed by treatment with RNase-free DNaseI (Epicentre, Madison, WI, USA) for one hour at 37 °C. cDNA synthesis reactions containing purified RNA, Affinityscript buffer, forward primer, and Affinityscript reverse transcriptase/RNase Block enzyme mix (Agilent Technologies, Cedarville, TX, USA) were incubated at 25 °C for five minutes to allow primer annealing, 45 °C for 45 min for cDNA synthesis, and finally at 95 °C for five minutes to heat kill the reverse transcriptase. .. Quantitation of RNA was performed by real-time PCR.

Article Title: A comparison between whole transcript and 3’ RNA sequencing methods using Kapa and Lexogen library preparation methods
Article Snippet: Paragraph title: Liver RNA purification ... RNA concentration was measured using the Qubit RNA BR Assay (cat# Q10211, Molecular Probes) and RNA integrity was measured with an Agilent 2200 Tapestation instrument using the Agilent RNA ScreenTape and Sample Buffer (cat#5067–5576 and cat#5067–5577, Agilent, Santa Clara, CA).

Polymerase Chain Reaction:

Article Title: Novel zinc-based fixative for high quality DNA, RNA and protein analysis
Article Snippet: The effects of 25 different fixative recipes on the fixed quality of tissues from C57BL/6 mice were investigated. .. Results from IHC, PCR, RT–PCR, RNA Agilent Bioanalyser and Real-Time PCR showed that a novel zinc-based fixative (Z7) containing zinc trifluoroacetate, zinc chloride and calcium acetate was significantly better than the standard zinc-based fixative (Z2) and neutral buffered formalin (NBF) for DNA, RNA and protein preservation. .. DNA sequences up to 2.4 kb in length and RNA fragments up to 361 bp in length were successfully amplified from Z7 fixed tissues, as demonstrated by PCR, RT–PCR and Real-Time PCR.

Article Title: ROCK signalling induced gene expression changes in mouse pancreatic ductal adenocarcinoma cells
Article Snippet: RNA quality was confirmed using the Agilent RNA ScreenTape assay and the Agilent 2200 TapeStation system, which revealed RNA integrity number equivalent (RINe ) values of 10 for all samples. .. Following RNA-seq, principal component analysis indicated that GFP:ER samples that had been treated with EtOH vehicle or 4HT clustered together while ROCK1:ER and ROCK2:ER samples treated with 4HT clustered together separate from the GFP:ER grouping , consistent with the conditional activation of ROCK catalytic activity observed by western blotting ( ).

Blocking Assay:

Article Title: Mechanisms that Determine the Differential Stability of Stx+ and Stx− Lysogens
Article Snippet: RNA was further purified by acid phenol extraction followed by chloroform: isoamyl alcohol extraction and precipitation. .. RNA was re-suspended in DNaseI buffer and RiboGuard, and residual genomic DNA was removed by treatment with RNase-free DNaseI (Epicentre, Madison, WI, USA) for one hour at 37 °C. cDNA synthesis reactions containing purified RNA, Affinityscript buffer, forward primer, and Affinityscript reverse transcriptase/RNase Block enzyme mix (Agilent Technologies, Cedarville, TX, USA) were incubated at 25 °C for five minutes to allow primer annealing, 45 °C for 45 min for cDNA synthesis, and finally at 95 °C for five minutes to heat kill the reverse transcriptase. .. Quantitation of RNA was performed by real-time PCR.

Chloramphenicol Acetyltransferase Assay:

Article Title: A comparison between whole transcript and 3’ RNA sequencing methods using Kapa and Lexogen library preparation methods
Article Snippet: DNA was digested on-column per the manufacturer’s instructions using the RNase-Free DNase Set (cat# 79254, Qiagen). .. RNA concentration was measured using the Qubit RNA BR Assay (cat# Q10211, Molecular Probes) and RNA integrity was measured with an Agilent 2200 Tapestation instrument using the Agilent RNA ScreenTape and Sample Buffer (cat5067–5576 and cat#5067–5577, Agilent, Santa Clara, CA). .. All samples had RINe values greater than 8.

Mouse Assay:

Article Title: Novel zinc-based fixative for high quality DNA, RNA and protein analysis
Article Snippet: The effects of 25 different fixative recipes on the fixed quality of tissues from C57BL/6 mice were investigated. .. Results from IHC, PCR, RT–PCR, RNA Agilent Bioanalyser and Real-Time PCR showed that a novel zinc-based fixative (Z7) containing zinc trifluoroacetate, zinc chloride and calcium acetate was significantly better than the standard zinc-based fixative (Z2) and neutral buffered formalin (NBF) for DNA, RNA and protein preservation.

Plasmid Preparation:

Article Title: Mechanisms that Determine the Differential Stability of Stx+ and Stx− Lysogens
Article Snippet: RNA was re-suspended in DNaseI buffer and RiboGuard, and residual genomic DNA was removed by treatment with RNase-free DNaseI (Epicentre, Madison, WI, USA) for one hour at 37 °C. cDNA synthesis reactions containing purified RNA, Affinityscript buffer, forward primer, and Affinityscript reverse transcriptase/RNase Block enzyme mix (Agilent Technologies, Cedarville, TX, USA) were incubated at 25 °C for five minutes to allow primer annealing, 45 °C for 45 min for cDNA synthesis, and finally at 95 °C for five minutes to heat kill the reverse transcriptase. .. As an internal control for RNA preparation, separate real-time PCR analyses were performed on the cDNA preparations of the E. coli uid gene transcript from the same RNA preparations as the PRM transcripts.

SYBR Green Assay:

Article Title: Mechanisms that Determine the Differential Stability of Stx+ and Stx− Lysogens
Article Snippet: RNA was re-suspended in DNaseI buffer and RiboGuard, and residual genomic DNA was removed by treatment with RNase-free DNaseI (Epicentre, Madison, WI, USA) for one hour at 37 °C. cDNA synthesis reactions containing purified RNA, Affinityscript buffer, forward primer, and Affinityscript reverse transcriptase/RNase Block enzyme mix (Agilent Technologies, Cedarville, TX, USA) were incubated at 25 °C for five minutes to allow primer annealing, 45 °C for 45 min for cDNA synthesis, and finally at 95 °C for five minutes to heat kill the reverse transcriptase. .. Quantitation of RNA was performed by real-time PCR.

RNA Extraction:

Article Title: Mechanisms that Determine the Differential Stability of Stx+ and Stx− Lysogens
Article Snippet: RNA was extracted from 0.5 mL of cells using the QuickExtract RNA extraction kit (Epicentre, Madison, WI, USA). .. RNA was re-suspended in DNaseI buffer and RiboGuard, and residual genomic DNA was removed by treatment with RNase-free DNaseI (Epicentre, Madison, WI, USA) for one hour at 37 °C. cDNA synthesis reactions containing purified RNA, Affinityscript buffer, forward primer, and Affinityscript reverse transcriptase/RNase Block enzyme mix (Agilent Technologies, Cedarville, TX, USA) were incubated at 25 °C for five minutes to allow primer annealing, 45 °C for 45 min for cDNA synthesis, and finally at 95 °C for five minutes to heat kill the reverse transcriptase.

Preserving:

Article Title: Novel zinc-based fixative for high quality DNA, RNA and protein analysis
Article Snippet: The effects of 25 different fixative recipes on the fixed quality of tissues from C57BL/6 mice were investigated. .. Results from IHC, PCR, RT–PCR, RNA Agilent Bioanalyser and Real-Time PCR showed that a novel zinc-based fixative (Z7) containing zinc trifluoroacetate, zinc chloride and calcium acetate was significantly better than the standard zinc-based fixative (Z2) and neutral buffered formalin (NBF) for DNA, RNA and protein preservation. .. DNA sequences up to 2.4 kb in length and RNA fragments up to 361 bp in length were successfully amplified from Z7 fixed tissues, as demonstrated by PCR, RT–PCR and Real-Time PCR.

Spectrophotometry:

Article Title: Novel zinc-based fixative for high quality DNA, RNA and protein analysis
Article Snippet: RNA samples were kept on ice and their concentrations measured using a Nanodrop spectrophotometer. .. RNA samples were prepared according to the Agilent 2100 Bioanalyser protocol and were loaded into the NanoChip or PicoChip and processed for 30 min. An equal amount of RNA was used for each experiment.

Concentration Assay:

Article Title: A comparison between whole transcript and 3’ RNA sequencing methods using Kapa and Lexogen library preparation methods
Article Snippet: DNA was digested on-column per the manufacturer’s instructions using the RNase-Free DNase Set (cat# 79254, Qiagen). .. RNA concentration was measured using the Qubit RNA BR Assay (cat# Q10211, Molecular Probes) and RNA integrity was measured with an Agilent 2200 Tapestation instrument using the Agilent RNA ScreenTape and Sample Buffer (cat#5067–5576 and cat#5067–5577, Agilent, Santa Clara, CA). .. All samples had RINe values greater than 8.

Lysis:

Article Title: A comparison between whole transcript and 3’ RNA sequencing methods using Kapa and Lexogen library preparation methods
Article Snippet: In brief, samples were homogenized in QIAzol lysis reagent using a rotor stator homogenizer. .. RNA concentration was measured using the Qubit RNA BR Assay (cat# Q10211, Molecular Probes) and RNA integrity was measured with an Agilent 2200 Tapestation instrument using the Agilent RNA ScreenTape and Sample Buffer (cat#5067–5576 and cat#5067–5577, Agilent, Santa Clara, CA).

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    Agilent technologies rna seq gene expression levels
    The percentages of probe sets in mapping groups A, B, C, and D. The percentages of Affymetrix probe sets in four mapping groups A, B, C, and D for the six <t>RNA-Seq</t> gene sets are shown in stacked bar charts. The data set comprises 62 Affymetrix Rat_230_2 arrays and 62 RNA-Seq assays from the same set of 62 rat liver RNA samples. The <t>microarray</t> data were normalized with MAS5, and the same RNA-Seq raw data were analyzed by six independent data analysis teams with a variety of analysis pipelines, that is, P1 (NCBI Magic), P2 (Novoalign with RefSeq gene models), P3 (Bwa + RefSeq RNAs), P4 (Tophat + HTSeq with RefSeq gene models), P5 (Bowtie + RSEM with Ensembl gene models), and P6 (Tophat + cufflinks de novo assembly). The Affymetrix probe sets (31,099 in total) were separately mapped to the six RNA-Seq gene sets. The mappings to P1, P2, P3, and P4 gene sets are based on the gene ID mapping approach, while mappings to P5 and P6 gene sets are based on the genome location mapping.
    Rna Seq Gene Expression Levels, supplied by Agilent technologies, used in various techniques. Bioz Stars score: 75/100, based on 9 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    The percentages of probe sets in mapping groups A, B, C, and D. The percentages of Affymetrix probe sets in four mapping groups A, B, C, and D for the six RNA-Seq gene sets are shown in stacked bar charts. The data set comprises 62 Affymetrix Rat_230_2 arrays and 62 RNA-Seq assays from the same set of 62 rat liver RNA samples. The microarray data were normalized with MAS5, and the same RNA-Seq raw data were analyzed by six independent data analysis teams with a variety of analysis pipelines, that is, P1 (NCBI Magic), P2 (Novoalign with RefSeq gene models), P3 (Bwa + RefSeq RNAs), P4 (Tophat + HTSeq with RefSeq gene models), P5 (Bowtie + RSEM with Ensembl gene models), and P6 (Tophat + cufflinks de novo assembly). The Affymetrix probe sets (31,099 in total) were separately mapped to the six RNA-Seq gene sets. The mappings to P1, P2, P3, and P4 gene sets are based on the gene ID mapping approach, while mappings to P5 and P6 gene sets are based on the genome location mapping.

    Journal: Genome Biology

    Article Title: An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

    doi: 10.1186/s13059-014-0523-y

    Figure Lengend Snippet: The percentages of probe sets in mapping groups A, B, C, and D. The percentages of Affymetrix probe sets in four mapping groups A, B, C, and D for the six RNA-Seq gene sets are shown in stacked bar charts. The data set comprises 62 Affymetrix Rat_230_2 arrays and 62 RNA-Seq assays from the same set of 62 rat liver RNA samples. The microarray data were normalized with MAS5, and the same RNA-Seq raw data were analyzed by six independent data analysis teams with a variety of analysis pipelines, that is, P1 (NCBI Magic), P2 (Novoalign with RefSeq gene models), P3 (Bwa + RefSeq RNAs), P4 (Tophat + HTSeq with RefSeq gene models), P5 (Bowtie + RSEM with Ensembl gene models), and P6 (Tophat + cufflinks de novo assembly). The Affymetrix probe sets (31,099 in total) were separately mapped to the six RNA-Seq gene sets. The mappings to P1, P2, P3, and P4 gene sets are based on the gene ID mapping approach, while mappings to P5 and P6 gene sets are based on the genome location mapping.

    Article Snippet: The consistency of Agilent microarray and RNA-Seq gene expression levels for human RNA samples.

    Techniques: RNA Sequencing Assay, Microarray

    Summary of the transferability of signature genes and predictive models between microarray and RNA-Seq data. The test results whether the parameters and signature genes of a model developed from one platform (microarray or RNA-Seq) can be used to build a model using data generated with the other platform (RNA-Seq or microarray) are shown in (a) for the three gene mappings A, B, and C separately; while the results whether a predictive model developed from one platform can be directly used to accurately predict the samples profiled with the other platform for gene mappings A and B are summarized for per sample z-scored data and without per sample z-scored data in (b) and (c) , respectively. Green and red arrows indicate the good and bad transferability from one platform to the other, respectively.

    Journal: Genome Biology

    Article Title: An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

    doi: 10.1186/s13059-014-0523-y

    Figure Lengend Snippet: Summary of the transferability of signature genes and predictive models between microarray and RNA-Seq data. The test results whether the parameters and signature genes of a model developed from one platform (microarray or RNA-Seq) can be used to build a model using data generated with the other platform (RNA-Seq or microarray) are shown in (a) for the three gene mappings A, B, and C separately; while the results whether a predictive model developed from one platform can be directly used to accurately predict the samples profiled with the other platform for gene mappings A and B are summarized for per sample z-scored data and without per sample z-scored data in (b) and (c) , respectively. Green and red arrows indicate the good and bad transferability from one platform to the other, respectively.

    Article Snippet: The consistency of Agilent microarray and RNA-Seq gene expression levels for human RNA samples.

    Techniques: Microarray, RNA Sequencing Assay, Generated

    A performance comparison of k-nearest neighbors (k-NN) models and their corresponding transferred models based on the TCGA AML data. For each of the two binary clinical endpoints and each of the three mapping groups A, B, and C, a set of 500 k-NN models were developed from microarray training data and used to predict microarray validation samples. The signature genes of each of the 500 microarray models were then used with all RNA-Seq training data for those genes to build an untrained RNA-Seq model to predict RNA-Seq validation samples. Finally, the average prediction accuracies of the 500 microarray models are plotted against those of the 500 corresponding RNA-Seq models (a) , with the per sample agreement better than chance evaluated with the Kappa statistic as shown in (b) . The transferability of the signature genes from RNA-Seq back to microarray data was conversely calculated. The 500 k-NN models trained from RNA-Seq data were used to predict RNA-Seq validation samples. Then the signature genes of each RNA-Seq model were used with all microarray training data for those genes to build an untrained k-NN model to predict microarray validation samples. The average accuracies of the 500 RNA-Seq models were then compared to those of the 500 corresponding microarray models (c) , with the per sample agreement better than chance assessed with the Kappa statistic as shown in (d) . The two symbols in each panel represent the two binary clinical endpoints with green, blue, and orange colors denoting mapping groups A, B, and C, respectively. In panels (b) and (d) , each symbol denotes the average Kappa statistic of the 500 pairs of model predictions; and each error bar shows the 95% confidence interval (CI) for the mean Kappa statistic. Each CI was calculated with the bootstrap estimation. No significant difference is observed between trained microarrays models and transferred RNA-Seq models (paired t-test P is 0.366) and between the trained RNA-Seq models and the transferred microarray models (paired t-test P is 0.269).

    Journal: Genome Biology

    Article Title: An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

    doi: 10.1186/s13059-014-0523-y

    Figure Lengend Snippet: A performance comparison of k-nearest neighbors (k-NN) models and their corresponding transferred models based on the TCGA AML data. For each of the two binary clinical endpoints and each of the three mapping groups A, B, and C, a set of 500 k-NN models were developed from microarray training data and used to predict microarray validation samples. The signature genes of each of the 500 microarray models were then used with all RNA-Seq training data for those genes to build an untrained RNA-Seq model to predict RNA-Seq validation samples. Finally, the average prediction accuracies of the 500 microarray models are plotted against those of the 500 corresponding RNA-Seq models (a) , with the per sample agreement better than chance evaluated with the Kappa statistic as shown in (b) . The transferability of the signature genes from RNA-Seq back to microarray data was conversely calculated. The 500 k-NN models trained from RNA-Seq data were used to predict RNA-Seq validation samples. Then the signature genes of each RNA-Seq model were used with all microarray training data for those genes to build an untrained k-NN model to predict microarray validation samples. The average accuracies of the 500 RNA-Seq models were then compared to those of the 500 corresponding microarray models (c) , with the per sample agreement better than chance assessed with the Kappa statistic as shown in (d) . The two symbols in each panel represent the two binary clinical endpoints with green, blue, and orange colors denoting mapping groups A, B, and C, respectively. In panels (b) and (d) , each symbol denotes the average Kappa statistic of the 500 pairs of model predictions; and each error bar shows the 95% confidence interval (CI) for the mean Kappa statistic. Each CI was calculated with the bootstrap estimation. No significant difference is observed between trained microarrays models and transferred RNA-Seq models (paired t-test P is 0.366) and between the trained RNA-Seq models and the transferred microarray models (paired t-test P is 0.269).

    Article Snippet: The consistency of Agilent microarray and RNA-Seq gene expression levels for human RNA samples.

    Techniques: Microarray, RNA Sequencing Assay

    The strategy for cross-platform gene mapping and the consistency of cross-platform gene expression measurements. The microarray probes/probe sets are mapped to RNA-Seq genes in one of two ways: public gene ID mapping or genome location mapping (a) . Using the gene ID mapping approach requires that one of the following public gene IDs be available: gene symbol, RefSeq transcript ID, Ensembl gene ID, or Entrez gene ID. Using the genome location mapping requires an RNA-Seq gene annotation file in either the Gene Transfer Format (GTF) or the General Feature Format (GFF). The process produces separate mapping lists for microarrays and RNA-Seq. Each of them consists of A, B, C, and D groups. Group A for microarrays corresponds to the group A in RNA-Seq. The microarray group B is a subset of RNA-Seq group C, and vice versa . The D group for microarrays and for RNA-Seq contain genes and probes/probe sets that cannot be mapped between the two platforms. The intensities of Affymetrix microarray probe sets in mapping groups A, B, and C are separately compared to those of RNA-Seq gene counts in panels (b) , (c) , and (d) for one of the eight RNA samples in the NCTR toxicogenomics data set. The microarray data are from Rat_230_2 arrays normalized with the MAS5 algorithm, and the RNA-Seq reads are from the Illumina GA II platform with the single-end 36 base pairs RNA-Seq protocol and gene counts from the P2 pipeline (Novoalign with RefSeq rat gene models). The mappings from microarray probe sets to RNA-Seq genes are based on the genome location mapping approach.

    Journal: Genome Biology

    Article Title: An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

    doi: 10.1186/s13059-014-0523-y

    Figure Lengend Snippet: The strategy for cross-platform gene mapping and the consistency of cross-platform gene expression measurements. The microarray probes/probe sets are mapped to RNA-Seq genes in one of two ways: public gene ID mapping or genome location mapping (a) . Using the gene ID mapping approach requires that one of the following public gene IDs be available: gene symbol, RefSeq transcript ID, Ensembl gene ID, or Entrez gene ID. Using the genome location mapping requires an RNA-Seq gene annotation file in either the Gene Transfer Format (GTF) or the General Feature Format (GFF). The process produces separate mapping lists for microarrays and RNA-Seq. Each of them consists of A, B, C, and D groups. Group A for microarrays corresponds to the group A in RNA-Seq. The microarray group B is a subset of RNA-Seq group C, and vice versa . The D group for microarrays and for RNA-Seq contain genes and probes/probe sets that cannot be mapped between the two platforms. The intensities of Affymetrix microarray probe sets in mapping groups A, B, and C are separately compared to those of RNA-Seq gene counts in panels (b) , (c) , and (d) for one of the eight RNA samples in the NCTR toxicogenomics data set. The microarray data are from Rat_230_2 arrays normalized with the MAS5 algorithm, and the RNA-Seq reads are from the Illumina GA II platform with the single-end 36 base pairs RNA-Seq protocol and gene counts from the P2 pipeline (Novoalign with RefSeq rat gene models). The mappings from microarray probe sets to RNA-Seq genes are based on the genome location mapping approach.

    Article Snippet: The consistency of Agilent microarray and RNA-Seq gene expression levels for human RNA samples.

    Techniques: Expressing, Microarray, RNA Sequencing Assay

    A performance comparison of k-nearest neighbors (k-NN) models and their corresponding transferred models. The comparison is based on the SEQC NB data set. For each of the six binary clinical endpoints and each of the three mapping groups A, B, and C, a set of 500 k-NN models were developed from microarray training data and used to predict microarray validation samples. The k parameter and signature genes of each of the 500 microarray models were then used with all RNA-Seq training data for those genes to build an untrained RNA-Seq model to predict RNA-Seq validation samples. Finally, the average prediction accuracies of the 500 microarray models are plotted against those of the 500 corresponding RNA-Seq models (a) , with the per sample agreement better than chance given by the Kappa statistic as shown in (b) . The transferability of the signature genes from RNA-Seq back to microarray data was conversely calculated. The 500 k-NN models trained from RNA-Seq data were used to predict RNA-Seq validation samples. Then the k parameter and signature genes of each RNA-Seq model were used with all microarray training data for those genes to build a microarray model to predict microarray validation samples. The average accuracies of the 500 RNA-Seq models are compared to those of the 500 corresponding microarray models (c) , with the per sample agreement better than chance given by the Kappa statistic as shown in (d) . The six symbols in each panel represent the six binary clinical endpoints with green, blue, and orange colors denoting mapping groups A, B, and C, respectively. In panels (b) and (d), each symbol denotes the average Kappa statistic for the 500 pairs of k-NNs models; and each error bar shows the 95% confidence interval (CI) for the mean Kappa statistic. Each CI was calculated with the bootstrap estimation.

    Journal: Genome Biology

    Article Title: An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

    doi: 10.1186/s13059-014-0523-y

    Figure Lengend Snippet: A performance comparison of k-nearest neighbors (k-NN) models and their corresponding transferred models. The comparison is based on the SEQC NB data set. For each of the six binary clinical endpoints and each of the three mapping groups A, B, and C, a set of 500 k-NN models were developed from microarray training data and used to predict microarray validation samples. The k parameter and signature genes of each of the 500 microarray models were then used with all RNA-Seq training data for those genes to build an untrained RNA-Seq model to predict RNA-Seq validation samples. Finally, the average prediction accuracies of the 500 microarray models are plotted against those of the 500 corresponding RNA-Seq models (a) , with the per sample agreement better than chance given by the Kappa statistic as shown in (b) . The transferability of the signature genes from RNA-Seq back to microarray data was conversely calculated. The 500 k-NN models trained from RNA-Seq data were used to predict RNA-Seq validation samples. Then the k parameter and signature genes of each RNA-Seq model were used with all microarray training data for those genes to build a microarray model to predict microarray validation samples. The average accuracies of the 500 RNA-Seq models are compared to those of the 500 corresponding microarray models (c) , with the per sample agreement better than chance given by the Kappa statistic as shown in (d) . The six symbols in each panel represent the six binary clinical endpoints with green, blue, and orange colors denoting mapping groups A, B, and C, respectively. In panels (b) and (d), each symbol denotes the average Kappa statistic for the 500 pairs of k-NNs models; and each error bar shows the 95% confidence interval (CI) for the mean Kappa statistic. Each CI was calculated with the bootstrap estimation.

    Article Snippet: The consistency of Agilent microarray and RNA-Seq gene expression levels for human RNA samples.

    Techniques: Microarray, RNA Sequencing Assay

    Flowcharts for evaluating the cross-platform transferability of signature genes and predictive models. Two analysis procedures were applied to evaluate the transferability of signature genes (a) and predictive models (b) . In (a) , microarray training data are used to develop 500 trained models through (c) to predict the microarray validation samples. The signature genes of each model are then used with the RNA-Seq training data to build an untrained RNA-Seq model using through (d) to predict the RNA-Seq validation samples. The performance of microarray models is finally compared to that of RNA-Seq models. The transferability of signature genes from RNA-Seq back to microarray data can conversely be calculated. While in (b) , both microarray and RNA-Seq data were z-scored prior to model development. Then microarray training data are used to develop 500 trained models to predict both microarray and RNA-Seq validation samples. The performance of models in predicting microarray data is compared to that in predicting RNA-Seq data. From RNA-Seq back to microarray is conversely examined. A trained model is developed through (c) . Briefly, training samples are randomly split in a 70/30 ratio. For each split, a series of models are developed using the 70% of training samples to predict the remaining 30%. The models are developed as follows: (1) all genes are first filtered with t-test P

    Journal: Genome Biology

    Article Title: An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

    doi: 10.1186/s13059-014-0523-y

    Figure Lengend Snippet: Flowcharts for evaluating the cross-platform transferability of signature genes and predictive models. Two analysis procedures were applied to evaluate the transferability of signature genes (a) and predictive models (b) . In (a) , microarray training data are used to develop 500 trained models through (c) to predict the microarray validation samples. The signature genes of each model are then used with the RNA-Seq training data to build an untrained RNA-Seq model using through (d) to predict the RNA-Seq validation samples. The performance of microarray models is finally compared to that of RNA-Seq models. The transferability of signature genes from RNA-Seq back to microarray data can conversely be calculated. While in (b) , both microarray and RNA-Seq data were z-scored prior to model development. Then microarray training data are used to develop 500 trained models to predict both microarray and RNA-Seq validation samples. The performance of models in predicting microarray data is compared to that in predicting RNA-Seq data. From RNA-Seq back to microarray is conversely examined. A trained model is developed through (c) . Briefly, training samples are randomly split in a 70/30 ratio. For each split, a series of models are developed using the 70% of training samples to predict the remaining 30%. The models are developed as follows: (1) all genes are first filtered with t-test P

    Article Snippet: The consistency of Agilent microarray and RNA-Seq gene expression levels for human RNA samples.

    Techniques: Microarray, RNA Sequencing Assay

    A performance comparison of k-nearest neighbors (k-NN) in predicting microarray and RNA-Seq validation samples. The comparison is based on the SEQC NB data set. In the comparison, both microarray log 2 intensity data and RNA-Seq log 2 counts were per sample z-scored. For each of the six binary clinical endpoints and each of the two mapping groups A and B, a set of 500 k-NN models were developed from microarray and RNA-Seq training data independently. Each set of k-NN models were then used to predict both microarray and RNA-Seq validation samples. The average prediction accuracies of the 500 microarray k-NN models in predicting microarray data are plotted against those in predicting RNA-Seq data (a) , with the per sample agreement better than chance evaluated with the Kappa statistic as shown in (b) ; while the average accuracies of the 500 RNA-Seq k-NN models in predicting RNA-Seq data are compared to those in predicting microarray data (c) , with the per sample agreement better than chance assessed with the Kappa statistic as shown in (d) . The six symbols in each panel represent the six binary clinical endpoints with green and blue colors denoting mapping groups A and B, respectively. In panels (b) and (d), each symbol denotes the average Kappa statistic of the 500 pairs of prediction results; and each error bar shows the 95% confidence interval (CI) for the mean Kappa statistic. Each CI was calculated with the bootstrap estimation.

    Journal: Genome Biology

    Article Title: An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

    doi: 10.1186/s13059-014-0523-y

    Figure Lengend Snippet: A performance comparison of k-nearest neighbors (k-NN) in predicting microarray and RNA-Seq validation samples. The comparison is based on the SEQC NB data set. In the comparison, both microarray log 2 intensity data and RNA-Seq log 2 counts were per sample z-scored. For each of the six binary clinical endpoints and each of the two mapping groups A and B, a set of 500 k-NN models were developed from microarray and RNA-Seq training data independently. Each set of k-NN models were then used to predict both microarray and RNA-Seq validation samples. The average prediction accuracies of the 500 microarray k-NN models in predicting microarray data are plotted against those in predicting RNA-Seq data (a) , with the per sample agreement better than chance evaluated with the Kappa statistic as shown in (b) ; while the average accuracies of the 500 RNA-Seq k-NN models in predicting RNA-Seq data are compared to those in predicting microarray data (c) , with the per sample agreement better than chance assessed with the Kappa statistic as shown in (d) . The six symbols in each panel represent the six binary clinical endpoints with green and blue colors denoting mapping groups A and B, respectively. In panels (b) and (d), each symbol denotes the average Kappa statistic of the 500 pairs of prediction results; and each error bar shows the 95% confidence interval (CI) for the mean Kappa statistic. Each CI was calculated with the bootstrap estimation.

    Article Snippet: The consistency of Agilent microarray and RNA-Seq gene expression levels for human RNA samples.

    Techniques: Microarray, RNA Sequencing Assay