An optimized workflow for transcriptomic analysis from archival paraformaldehyde-fixed retinal tissues collected by laser capture microdissection
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ABSTRACT:
PROVIDER: PRJNA1092667 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR28477717.fastq.gz | Fastqsanger.gz | |||
| SRR28477718.fastq.gz | Fastqsanger.gz | |||
| SRR28477719.fastq.gz | Fastqsanger.gz | |||
| SRR28477720.fastq.gz | Fastqsanger.gz | |||
| SRR28477721.fastq.gz | Fastqsanger.gz |
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Project description:RNA sequencing (RNA-seq) coupled with laser capture microdissection (LCM) is a powerful tool for transcriptomic analysis in unfixed fresh-frozen tissues. Fixation of ocular tissues for immunohistochemistry commonly involves the use of paraformaldehyde (PFA) followed by embedding in Optimal Cutting Temperature (OCT) medium for long-term cryopreservation. However, the quality of RNA derived from such archival PFA-fixed/OCT-embedded samples is often compromised, limiting its suitability for transcriptomic studies. In this study, we aimed to develop a methodology to extract high-quality RNA from PFA-fixed canine eyes by utilizing LCM to isolate retinal tissue. We demonstrate the efficacy of an optimized LCM and RNA purification protocol for transcriptomic profiling of PFA-fixed retinal specimens. We compared four pairs of canine retinal tissues, where one eye was subjected to PFA-fixation prior to OCT embedding, while the contralateral eye was embedded fresh frozen (FF) in OCT without fixation. Since the mRNA obtained from PFA-fixed retinas were contaminated with genomic DNA, we employed two rounds of DNase I treatment to obtain RNA suitable for RNA-seq. Notably, the quality of sequencing reads and gene sets identified from both PFA-fixed and FF tissues were nearly identical. In summary, our study introduces an optimized workflow for transcriptomic profiling from PFA-fixed archival retina. This refined methodology paves the way for improved transcriptomic analysis of preserved ocular tissue, bridging the gap between optimal sample preservation and high-quality RNA data acquisition.
2024-05-15 | GSE262625 | GEO
Project description:BACKGROUND: Array Comparative Genomic Hybridization (aCGH) is a rapidly evolving technology that still lacks complete standardization. Yet, it is of great importance to obtain robust and reproducible data to enable meaningful multiple hybridization comparisons. Special difficulties arise when aCGH is performed on archival formalin-fixed, paraffin-embedded (FFPE) tissue due to its variable DNA quality. Recently, we have developed an effective DNA quality test that predicts suitability of archival samples for BAC aCGH. METHODS: In this report, we first used DNA from a cancer cell-line (SKBR3) to optimize the aCGH protocol for automated hybridization, and subsequently optimized and validated the procedure for FFPE breast cancer samples. We aimed for highest throughput, accuracy, and reproducibility applicable to FFPE samples, which can also be important in future diagnostic use. RESULTS: Our protocol of automated array-CGH on archival FFPE ULS-labeled DNA showed very similar results compared with published data and our previous manual hybridization method. CONCLUSION: This report combines automated aCGH on unamplified archival FFPE DNA using non-enzymatic ULS labeling, and describes an optimized protocol for this combination resulting in improved quality and reproducibility. In this study, we optimized the BAC araay-CGH protocol for automated hybridization for FFPE breast cancer samples. We have tested hybridization temperature and duration, different hybridization buffer conditions, and post-hybridization washing.
2010-06-12 | E-GEOD-7122 | biostudies-arrayexpress
Project description:BACKGROUND: Array Comparative Genomic Hybridization (aCGH) is a rapidly evolving technology that still lacks complete standardization. Yet, it is of great importance to obtain robust and reproducible data to enable meaningful multiple hybridization comparisons. Special difficulties arise when aCGH is performed on archival formalin-fixed, paraffin-embedded (FFPE) tissue due to its variable DNA quality. Recently, we have developed an effective DNA quality test that predicts suitability of archival samples for BAC aCGH. METHODS: In this report, we first used DNA from a cancer cell-line (SKBR3) to optimize the aCGH protocol for automated hybridization, and subsequently optimized and validated the procedure for FFPE breast cancer samples. We aimed for highest throughput, accuracy, and reproducibility applicable to FFPE samples, which can also be important in future diagnostic use. RESULTS: Our protocol of automated array-CGH on archival FFPE ULS-labeled DNA showed very similar results compared with published data and our previous manual hybridization method. CONCLUSION: This report combines automated aCGH on unamplified archival FFPE DNA using non-enzymatic ULS labeling, and describes an optimized protocol for this combination resulting in improved quality and reproducibility.
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Project description:Spatial tissue proteomics integrating whole-slide imaging, laser microdissection and ultrasensitive mass spectrometry is a powerful approach to link cellular phenotypes to functional proteome states in (patho)physiology. To be applicable to large patient cohorts and low sample input amounts, including single-cell applications, loss-minimized and streamlined end-to-end workflows are key. We here introduce an automated sample preparation protocol for laser microdissected samples utilizing the cellenONE® robotic system, which has the capacity to process 192 samples in three hours. Following laser microdissection collection directly into the proteoCHIP LF 48 or EVO 96 chip, our optimized protocol facilitates lysis, formalin de-crosslinking and tryptic digest of low-input archival tissue samples. The seamless integration with the Evosep ONE LC system by centrifugation allows ‘on-the-fly’ sample clean-up, particularly pertinent for laser microdissected workflows. We validate our method in human tonsil archival tissue, where we profile proteomes of spatially-defined B-cell, T-cell and epithelial microregions of 4,000 µm2 to a depth of ~2,000 proteins and with high cell type specificity. We finally provide detailed equipment templates and experimental guidelines for broad accessibility.
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Project description:An optimized RNA-seq workflow for isolating single nuclei from clinical biopsies
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Project description:Archival chromatin sequencing in formalin-fixed mouse specimens
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Project description:BackgroundArray Comparative Genomic Hybridization (aCGH) is a rapidly evolving technology that still lacks complete standardization. Yet, it is of great importance to obtain robust and reproducible data to enable meaningful multiple hybridization comparisons. Special difficulties arise when aCGH is performed on archival formalin-fixed, paraffin-embedded (FFPE) tissue due to its variable DNA quality. Recently, we have developed an effective DNA quality test that predicts suitability of archival samples for BAC aCGH.MethodsIn this report, we first used DNA from a cancer cell-line (SKBR3) to optimize the aCGH protocol for automated hybridization, and subsequently optimized and validated the procedure for FFPE breast cancer samples. We aimed for highest throughput, accuracy, and reproducibility applicable to FFPE samples, which can also be important in future diagnostic use.ResultsOur protocol of automated array-CGH on archival FFPE ULS-labeled DNA showed very similar results compared with published data and our previous manual hybridization method.ConclusionThis report combines automated aCGH on unamplified archival FFPE DNA using non-enzymatic ULS labeling, and describes an optimized protocol for this combination resulting in improved quality and reproducibility.
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Project description:The use of nucleic acids from formalin-fixed paraffin-embedded (FFPE) tissues for high-throughput molecular techniques, such as microarray gene expression profiling has become widespread in molecular research area. However, working with FFPE tissues is challenging because of degradation, cross-linking with proteins, and RNA chemical modifications. Also, there is no generally accepted procedure for RNA extraction to microarray analysis. Thus, there is a need for a standardized workflow for FFPE samples to study microarray transcriptome profiling. Therefore, the main purpose of this study was to conduct a standardized process from deparaffinization to RNA extraction and microarray gene expression analysis. Firstly, deparaffinization procedure was optimized for FFPE samples and then Trizol, PicoPure RNA isolation kit, and Qiagen RNeasy FFPE kit performances were compared in terms of yield and purity. Finally, two different cRNA/cDNA preparation and labeling protocols with two different array platforms (Affymetrix Human Genome U133 Plus 2.0 and U133_X3P) were also evaluated to determine which combination gives the best percentage of present call. Our optimization study shows that the Qiagen RNeasy FFPE kit with modified deparaffinization step gives better results (RNA quantity and quality) than the other two isolation kits. The Ribo-SPIA protocol and U133_X3P array combination gave a significantly higher percentage of present calls than the 3’ IVT cDNA amplification and labeling system. However, no significant differences were found between the two array platforms. These results present a workflow for microarray gene expression profiling of FFPE tissues. The findings also indicate that sufficient quality gene expression data can be obtained from FFPE-derived RNA.
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Project description:Reversible protein phosphorylation represents a key mechanism by which signals are transduced in eukaryotic cells. Dysregulated phosphorylation is also a hallmark of carcinogenesis and represents key drug targets in the precision medicine space. Thus, methods that preserve phosphoprotein integrity in the context of clinical tissue analyses are crucially important in cancer research. Here we investigated the impact of UV laser microdissection (UV LMD) and IR laser capture microdissection (IR LCM) on phosphoprotein abundance of key cancer signaling protein targets assessed by reverse-phase protein microarray (RPPA). Tumor epithelial cells from consecutive thin sections obtained from four high-grade serous ovarian cancers were harvested using either UV LMD or IR LCM methods. Phosphoprotein abundances for ten phosphoproteins that represent important drug targets were assessed by RPPA and revealed no significant differences in phosphoprotein integrity from those obtained using higher-energy UV versus the lower-energy IR laser methods.
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