Experimental Design for Laser Microdissection RNA-Seq: Lessons from an Analysis of Maize Leaf Development
March 5th, 2017
Many developmentally important genes have cell- or tissue-specific expression patterns. This paper describes LM RNA-seq experiments to identify genes that are differentially expressed at the maize leaf blade-sheath boundary and in lg1-R mutants compared to wild-type. The experimental considerations discussed here apply to transcriptomic analyses of other developmental phenomena.
The overall goal of this method is the quantify transcript accumulation in specific cells or cellular domains so that comparisons can be made between different domains or between equivalent domains in mutant and wild type samples. This method can help answer key questions in developmental biology such as how organ domains are specified or how specific mutations affect gene expression. The main advantage of this technique is that transcript accumulation can be quantified in minute, precisely defined domains that are too small to be dissected by hand.
Prior to starting this procedure, grow flats of maize seedlings under standard conditions to two weeks old. To dissect shoot apices for lateral sections, first excise a seedling just below the soil line. Then use a razor blade to remove thin slices from the base of the stem until an oval of calm encircled by one or two mature leaves is visible.
Make another cut approximately 10 millimeters above the base. This 10-millimeter segment contains the shoot apical meristem in young leaf primordia. Turn the 10-millimeter segment so the base is facing up.
Make two cuts parallel to the lateral axis to obtain a slide of tissue two to three millimeters thick. Discard the outer two portions and retain the central slice for fixation and embedding. Immerse the tissue slice in approximately 10 milliliters of farmers fix in a glass vial on ice.
After all samples have been dissect, apply vacuum to remove air bubbles and aid penetration of fixative. Hold onto the vacuum for 10 minutes, and then slowly release the vacuum. Replace the fixative, and incubate at four degrees Celsius overnight with gentle shaking.
On the following day, continue to process the tissues for embedding as described in the text protocol. To cast paraffin blocks, place embedding molds on a hot plate of the tissue-embedding station, and use forceps to transfer the tissue samples to the embedding molds with the cut surface facing down. Place the embedding ring on the top of the mold.
Top up each mold with melted paraffin. Transfer the molds to a cold plate until the paraffin has solidified. Store the paraffin blocks in an airtight container with silica gel at four degrees Celsius.
Sections are cut from paraffin blocks on a microtome following standard procedures, and median sections that include the shoot apical meristem are selected for mounting. To mount the sections on slides, place slides that are either RNase-free or baked on a 42 degrees Celsius slide warmer. Apply several drops of 50%ethanol solution to cover each slide.
Gently lay sections on slide, and float the sections on the ethanol solution until they have expanded. Next, tilt the slide and remove excess ethanol solution by aspiration with a disposable transfer pipet. Use lint-free wipes to wick away any additional ethanol solution.
Dry the slides at 42 degrees Celsius for several hours or overnight. When the slides are dry, store them in an airtight container with silica gel at four degrees Celsius. Deparaffinize the slides on the day of the microdissection.
Prepare three glass Coplin jars, two jars that contain about 50 milliliters of 100%xylenes and one jar containing about 50 milliliters of 100%ethanol. Immerse the slides in xylenes one for two minutes, xylenes two for two minutes, and 100%ethanol for one minute. Drain the slides on lint-free wipes and air-dry it at room temperature.
To begin this procedure, secure the slides on the stage of the laser microdissection microscope. A critical factor in the success of laser microdissection in RNasic experiments is the use of morphological and molecular markers to select precise domains for microdissection. Examine the slides using a 5X objective and identify the five most median sections on each slide using the shoot apical meristem apex as the central reference point.
Next, use either a 10X or 20X objective to identify the position of the ligule on the plastochron seven leaf primordium of each section. The ligule will be visibile as a bump protruding from the adaxial surface of the leaf primordium. Use the drawing tool of the laser microdissection software to mark this position.
Select the freehand drawing icon, move the cursor to the appropriate position, and click and drag the mouse to draw. The next step is to use the ruler and the rectangular drawing tool to measure 100 micrometer-high rectangles centered on a ligule of each section as the ligule samples. To use the ruler tool, select the ruler icon, move the cursor to one end of the region to be measured, and then click and drag to measure the region.
The length of the ruler will be shown on the screen. Use the ruler tool to measure a 100-micrometer segment centered on a ligule. To draw a rectangle, select the straight line drawing tool and draw four straight lines.
In the same manner, measure 100-micrometer rectangles positioned 50 micrometers above and below the ligule rectangle. These will be the blade and sheath samples. Microdissect the measured rectangles using the laser cut function to cut through the tissue section along the outline of the selected domain, and the catapult function to propel the rectangle of the tissue off the slide into the lid of the tube.
Collect ligule, blade, and sheath samples in separate tubes. Use the same procedure to microdissect blade, ligule, and sheath adaxial epidermal samples from plastochron seven leaf primordia. Lastly, apply RNA extraction buffer to the microdissected tissue and proceed with RNA extraction, RNA amplification, library construction, sequencing, and bioinformatics analysis as described in the manuscript.
When transcript accumulation was analyzed and all cell layers of the blade, ligule, and sheath regions, 2, 359 differentially expressed genes were found. In the adaxial epidermal blade, ligule, and sheath regions, 3, 128 differentially expressed genes were found. Laser microdissection, RLM, RNA sequencing, and in situ hybridization analyses gave consistent results as illustrated by these representative genes.
The cartoons on the left illustrate LM of all cell layers, and the cartoons on the right illustrate LM of adaxial epidermis only. The arrowheads in the images indicate emerging ligules. Ligules one transcript accumulation was significantly higher in the ligule in both all cell layers and epidermal LM.Narrow sheath one was significantly upregulated in the ligule region in both the all cell layers LM and the adaxial epidermis LM, and accumulates specifically in the tip of the emerging ligule.
A gene of unknown function had a higher mean recount in the ligule epidermal LM than in the all layers LM.This transcript accumulates most strongly in epidermal cells. The fourth gene, Zm PIN1a was not significantly differentially expressed in the analysis of all cell layers but was significantly upregulated in the ligule in the epidermis-only analysis. Its high expression in vascular tissue may have confounded differences in transcript accumulation in the epidermis when all cell layers were collected.
When attempting this procedure, it's important to remember that the choice of cellular domains to microdissect and compare, and the accuracy of the microdissections are crucial to the success of the experiments.
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Overview
This study focuses on quantifying transcript accumulation in specific cellular domains in maize. It highlights the importance of understanding gene expression differences at the leaf blade-sheath boundary and in lg1-R mutants compared to wild-type.
Key Study Components
Area of Science
- Developmental Biology
- Gene Expression
- Transcriptomics
Background
- Developmentally important genes exhibit cell- or tissue-specific expression patterns.
- Understanding these patterns is crucial for insights into organ domain specification.
- Mutations can significantly affect gene expression, impacting developmental processes.
- Transcript accumulation can be quantified in small, defined domains.
Purpose of Study
- To identify differentially expressed genes at the maize leaf blade-sheath boundary.
- To compare gene expression in lg1-R mutants with wild-type samples.
- To provide a method for analyzing transcriptomic data in developmental biology.
Methods Used
- LM RNA-seq experiments to analyze gene expression.
- Dissection of shoot apices from maize seedlings for lateral sectioning.
- Standard growth conditions for maize seedlings prior to experimentation.
- Quantification of transcript accumulation in specific cellular domains.
Main Results
- Identification of genes with differential expression patterns at the leaf blade-sheath boundary.
- Comparison of gene expression in lg1-R mutants versus wild-type samples.
- Demonstration of the method's effectiveness in analyzing small cellular domains.
- Insights into how specific mutations influence gene expression during development.
Conclusions
- The study provides a valuable method for transcriptomic analysis in developmental biology.
- Understanding gene expression patterns can inform on organ development and mutation effects.
- This approach can be applied to other developmental phenomena beyond maize.
Frequently Asked Questions
Executive Industry Relevance
Laser Microdissection RNA-Seq enables precise quantification of transcript accumulation in narrowly defined plant tissue domains, addressing the challenge of spatially restricted gene expression that is often masked in whole-organ analyses. This approach enhances predictive confidence in target validation by isolating the biological context of gene regulation, supporting risk-adjusted decisions in early discovery and functional genomics pipelines. Accurate domain selection and microdissection fidelity are critical for generating reproducible, actionable transcriptomic data that inform portfolio triage and mechanistic de-risking.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables interrogation of gene function in specific developmental domains, clarifying pathway roles.
- Supports biological de-risking by isolating the effects of mutations or perturbations on gene expression.
- Improves predictive confidence for target selection by revealing spatially restricted differential expression.
- Facilitates portfolio triage by distinguishing context-dependent gene activity.
Screening & Assay Development
- Prepares validated tissue domains for downstream transcriptomic workflows.
- Standardizes sample selection using morphological and molecular landmarks for reproducibility.
- Generates quantitative gene expression outputs suitable for comparative analysis.
- Enables reliable evaluation of candidate genes or pathways in defined biological contexts.
Translational & Preclinical Research
- Aligns transcriptomic findings with disease-relevant or developmental biomarkers when applicable.
- Supports continuity from discovery through preclinical validation by enabling precise domain-specific analyses.
- Provides mechanistic de-risking by clarifying the spatial context of gene regulation.
Pipeline & Workflow Integration
This method integrates into the discovery continuum from early hypothesis testing through lead identification, supporting both target validation and mechanistic studies in plant and potentially other model systems.
- Discovery Biology: Facilitates hypothesis testing and pathway clarification by quantifying transcripts in defined domains.
- Screening: Delivers reproducible, quantitative gene expression data for assay development and screening readiness.
- Analytics: Provides differential expression measurements that enable robust comparison across conditions or genotypes.
- Translational Research: Supports biomarker alignment and preclinical continuity when spatial gene expression is relevant.
- Enterprise Reuse: Establishes a reusable workflow for spatial transcriptomics across diverse developmental or disease models.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in target validation.
- Operational Value: Enhances standardization, reproducibility, and scalability of transcriptomic analyses.
- Strategic Value: Improves go/no-go decisions and capital efficiency by clarifying biological context.
- Portfolio Impact: Enables risk-adjusted prioritization and advancement of targets based on spatial gene expression data.
Implementation Considerations
- Requires expertise in histology, microdissection, and transcriptomic analysis.
- Demands access to laser microdissection instrumentation and RNA-seq infrastructure.
- Necessitates rigorous cross-team standardization of sample selection and domain definition.
- May require adaptation for different tissue types or developmental stages.
- Precision in domain selection and microdissection is critical for data quality and interpretability.
Biopharma FAQs
Chapters in this video
0:05
Title
0:45
Tissue Fixation and Processing
3:03
Sectioning and Slide Preparation
4:57
Microdissection of Blade, Ligule, and Sheath Samples from Plastochron 7 Leaf Primordia
7:48
Results: Laser Microdissection RNA Sequencing Identifies Differentially Expressed Genes in Maize Leaf
9:38
Conclusion
