Transcriptome Profiling of In-Vivo Produced Bovine Pre-implantation Embryos Using Two-color Microarray Platform
January 30th, 2017
Microarray technology allows quantitative measurement and gene expression profiling of transcripts on a genome-wide basis. Therefore, this protocol provides an optimized technical procedure in a two-color custom made bovine array using Day 7 bovine embryos to demonstrate the feasibility of using low amount of total RNA.
The overall goal of this video is to provide an optimized technical procedure using a two-color custom-made bovine array using a low amount of total RNA from day seven bovine embryos. This method can help answer key questions regarding embryonic loss in high-producing dairy cows and questions about embryonic quality relative to gene expression in the developing embryo prior to implantation. The advantage of this technique is that we can study gene expression using picogram level of total RNA extracted from single embryos.
This method can provide insight into the factor affecting the survival of in vivo produced bovine pre-implantation embryos. This can also help improve reproductive technologies such as in vitro embryo productions. To begin the procedure, prepare snap frozen bovine embryos in a microcentrifuge tube from a column-based pico scale RNA extraction kit.
Add 10 microliters of lysis buffer to the tube, and incubate the embryos at 42 degrees Celsius for 30 minutes. Then, centrifuge the tube for two minutes at 800 times G.Pipette 250 microliters of conditioning buffer into the purification column filter membrane, and incubate the column for five minutes at room temperature. Centrifuge the collection tube at 16, 000 times G for one minute to finish preconditioning the column.
Add 10 microliters of 70%ethanol to the mixture of lysis buffer and embryos and mix well. Then, load the mixture onto the purification column. Centrifuge the column for two minutes at 100 times G, and then at 16, 000 times G for 30 seconds.
Add 100 microliters of the first wash buffer to the column, and centrifuge at 8, 000 times G for one minute. Using a DNase kit, mix five microliters of stock solution with 35 microliters of buffer, and mix by gently inverting the closed tube. Then, load the DNase mixture onto the purification column membrane, and incubate for 15 minutes at room temperature.
Add 40 microliters of the first wash buffer to the column, and centrifuge at 8, 000 times G for 15 seconds. Then, add 100 microliters of the second wash buffer, and centrifuge for a minute. Add another portion of the second wash buffer to the column, and centrifuge for two minutes at 16, 000 times G.Transfer the purification column to another microcentrifuge tube, and load 11 microliters of elution buffer onto the column membrane.
Incubate the column for one minute at room temperature. Centrifuge the column for one minute at 1, 000 times G, and then for another minute at 16, 000 times G.Check the quality and quantity of the eluted RNA, and then store the sample in negative 80 degrees Celsius. Using an amplification kit, amplify 100 picograms of high-quality RNA.
Evaluate the size range of the amplified aRNA with fluorescence-based quantitation. Then, determine the concentration of aRNA by spectrophotometry. Prepare two micrograms of the amplified aRNA for fluorescent labeling with a standard kit.
Set up an ozone box in a darkroom, and wait until the ozone level decreases to 0.001 parts per million. Place a darkroom filter over the light. Then, bring the sample into the ozone box and add two microliters each of cyanine five dye and labeling buffer.
With the sample under a safe light, add RNase free water to achieve a total volume of 20 microliters. Gently mix the sample, and then, incubate the tube in a thermocycler at 85 degrees Celsius for 15 minutes. Cool the sample on ice for one minute, and then, spin down the sample.
Clean up the labeled and amplified aRNA with an RNA extraction kit. Using the appropriate type of spectrometer, determine the concentration of labeled, amplified aRNA. Prepare a second sample of amplified aRNA labeled with cyanine three dye.
Store the aRNA samples at negative 80 degrees Celsius for up to three days. Combine 825 nanograms each of Cy3 and 5-labeled aRNA. Add to this the blocking buffer and the fragmentation buffer.
Incubate the mixture at 60 degrees Celsius for 15 minutes, and then, cool on ice for one minute. Add 55 microliters hybridization buffer, and mix well without introducing air bubbles. Centrifuge the mixture at 11, 300 times G for one minute.
Load 100 microliters of sample onto the array slide, and seal the slide in the hybridization chamber. Hybridize the sample for 17 hours at 65 degrees Celsius while rotating at 10 rotations per minute. Prepare an ozone-scavenging stabilizing and drying solution.
Wash the arrays, taking precautions to minimize exposure to ozone, and then, immerse them in the stabilizing and drying solution for 30 seconds. Ensure the array surface is dry and free of dust. Store the arrays in a dark location.
Turn on the microarray scanner, and wait until it is ready to scan. Then, load the array with the barcode to the left. Perform a spot analysis, and save the data as a GPR file.
In statistical analysis software, normalize and analyze the data. Calculate the positive spot selection threshold, and view the plot of hybridized and background signals. Perform a Loess normalization within array, and then a quantile between arrays normalization.
Export the normalized data to a spreadsheet file. Use the all positive signals in a microarray data repository to create an ID list of selected unique genes. Upload the ID list to a protein classification and analysis database, choosing bos taurus as the organism, and perform a default statistical overrepresentation test.
Following two-round amplification, the fragments are very similar in size and of good quality. Successful amplification by this method should yield at least a thousand-fold increase of aRNA. A high-quality microarray image has high spot intensity and low background intensity on both channels.
If the background intensity is too high, signal resolution will be poor. About 46%of the spots were above background, from which 6, 765 unique RNA transcripts expressed in the blastocyst were isolated. A statistical overrepresentation test indicated that the top 10 gene ontology terms represented active cellular division processes.
The development of this technique has allowed researchers in the area of animal reproduction to explore embryonic gene expression and evaluate how various factors effect the developing embryo. This technique has also been developed in other important species, such as the pig. Following this procedure, other methods such as quantitative PCR can be used to validate microarray results.
After watching this video, you should have a good understanding of how to extract RNA from embryos as well as how to amplify and label RNA to perform two-color microarray analysis.
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Overview
This protocol outlines an optimized technical procedure using a two-color custom-made bovine array to analyze gene expression in day seven bovine embryos. The method allows for the use of low amounts of total RNA, providing insights into embryonic quality and factors affecting embryo survival.
Key Study Components
Area of Science
- Neuroscience
- Embryology
- Gene Expression
Background
- Microarray technology enables genome-wide gene expression profiling.
- Understanding embryonic loss in dairy cows is crucial for improving reproductive technologies.
- Low RNA input methods can enhance studies on single embryos.
- Gene expression analysis can inform practices in in vitro embryo production.
Purpose of Study
- To demonstrate the feasibility of using low amounts of total RNA from bovine embryos.
- To investigate gene expression related to embryonic quality prior to implantation.
- To provide insights into factors affecting the survival of bovine pre-implantation embryos.
Methods Used
- Preparation of snap frozen bovine embryos.
- Utilization of a column-based pico scale RNA extraction kit.
- Implementation of a two-color custom-made bovine array.
- Quantitative measurement of gene expression at picogram RNA levels.
Main Results
- Successful profiling of gene expression using minimal RNA.
- Insights into embryonic quality and factors influencing survival.
- Potential improvements in reproductive technologies.
- Demonstration of the method's feasibility for future studies.
Conclusions
- The protocol provides a valuable tool for studying bovine embryo gene expression.
- Low RNA input methods can facilitate research on embryonic development.
- This approach may lead to advancements in reproductive practices in dairy farming.
Frequently Asked Questions
Executive Industry Relevance
This protocol enables genome-wide gene expression profiling from picogram-level RNA extracted from single bovine embryos, addressing a critical bottleneck in reproductive biology research. By providing quantitative transcriptomic data from in vivo-produced pre-implantation embryos, the method supports mechanistic de-risking of embryonic loss factors in high-producing dairy cattle. The approach offers translational value for target validation in reproductive therapeutics and predictive confidence in embryo quality assessment pipelines.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Scientific Value: Enables interrogation of transcriptional networks governing embryonic survival and quality prior to implantation.
- Operational Value: Facilitates functional target validation by linking gene expression patterns to phenotypic outcomes in embryo development.
- Predictive Value: Supports portfolio triage by identifying molecular signatures associated with viable versus non-viable embryos.
Screening & Assay Development
- Assay Readiness: Generates standardized, reproducible transcriptomic profiles suitable for biomarker discovery and assay standardization.
- Scalability: Two-color microarray design increases technical replication and minimizes variability, enabling robust cross-sample comparisons.
- Platform Utility: Creates a reusable foundation for downstream validation via qPCR or functional screening of candidate genes.
Translational & Preclinical Research
- Disease Relevance: Provides a bovine model system with developmental parallels to human pre-implantation embryogenesis for mechanistic studies.
- Translational Continuity: Connects discovery-phase gene expression findings to preclinical evaluation of factors affecting embryo survival.
- Risk-Adjusted Advancement: Enables data-driven decisions on reproductive technology interventions based on expression profiles of key developmental pathways.
Pipeline & Workflow Integration
The method fits within the early discovery continuum, supporting hypothesis-driven target identification and mechanistic validation before progressing to functional assays or in vivo validation studies.
- Discovery Biology: Supports pathway clarification and biological de-risking by isolating differentially expressed transcripts associated with embryo quality and survival.
- Screening: Delivers quantitative, normalized expression outputs that enable reliable comparison of genetic or environmental conditions on embryonic development.
- Analytics: Employs Loess and quantile normalization with statistical overrepresentation testing to derive actionable gene ontology insights from microarray data.
- Translational Research: Aligns with biomarker discovery efforts by identifying conserved processes like active cellular division as top-ranked functional terms in blastocyst-stage embryos.
- Enterprise Reuse: Establishes a standardized RNA-to-data workflow applicable across livestock species and adaptable to other mammalian embryo models.
Operational & Enterprise Impact
- Scientific Value: Reduces mechanistic ambiguity in embryonic loss by providing genome-scale expression data from clinically relevant developmental stages.
- Operational Value: Enables high-sensitivity detection from minimal RNA input, standardizing low-input workflows for precious or limited biological samples.
- Strategic Value: Improves go/no-go decision-making in reproductive technology development by linking molecular profiles to embryonic viability outcomes.
- Portfolio Impact: Supports risk-adjusted prioritization of targets or interventions based on enrichment of functionally coherent gene networks.
Implementation Considerations
- Requires expertise in RNA handling, enzymatic amplification, and fluorescent labeling techniques to prevent sample degradation.
- Dependent on access to microarray scanners, hybridization chambers, and ozone-controlled environments to maintain signal integrity.
- Necessitates cross-team standardization of RNA quality metrics, labeling efficiency, and hybridization conditions for reproducible results.
- Involves adaptation considerations when transferring the protocol to different embryo stages, species, or sample types with varying RNA yield.
- Practical limitations include the requirement for amplified RNA input and potential bias introduced during two-round amplification steps.
