Optimized full-length single nuclei RNA sequencing (snRNA-seq) to propel crop innovation

• Achieve higher purity and lower background nuclei suspensions from challenging pollen samples

• Reveal distinct nuclei types using snRNA-seq libraries prepared with the SMART-Seq Pro Application Kit - 2 Chip on the ICELL8 cx Single-Cell System

Improving transcriptomics for crop development

Genetic analysis of plant biology supports discoveries—for instance, revealing genes tied to agriculturally important traits or regulatory processes that breeders can harness to achieve crop improvement (Underwood et al. 2022; Fuchs et al 2017). Single-nuclei RNA sequencing (snRNA-seq) has demonstrated value in the characterization of transcriptomes of, for instance, seedlings (Sunaga-Franze et al. 2021) and has yielded insights into the regulation of pollen development (Ichino et al. 2022). However, several challenges remain, particularly in obtaining high-quality nuclei suspensions from crop pollen for high-throughput snRNA-seq.

To leverage the advantages of snRNA-seq, researchers demonstrated the potential of a workflow (Figure 1) combining the power of KeyGene’s nuclei isolation procedure and Takara Bio’s SMART-Seq Pro Application Kit - 2 Chip on the ICELL8 cx Single-Cell System for full-length transcriptome analysis of vegetative and generative nuclei in tobacco pollen. The procedure could be applied in other tissues, thus serving as a valuable new resource for single-nuclei transcriptomics research into mechanisms governing the development and function of those tissues.

Figure 1: Overview of the integration of high-purity nuclei suspensions with the SMART-Seq Pro application kit on the ICELL8 cx system.

Achieve higher purity and lower background nuclei suspensions from challenging pollen samples

Pollen nuclei are challenging to isolate due to a stiff external cell wall that protects inner structures from environmental damage. Isolating pollen nuclei requires precise control—too much mechanical force can destroy the nuclei, and too little can result in failure to release nuclei. Traditional methods lack this control, resulting in low-purity and high-background samples. To mitigate these challenges, KeyGene developed a novel isolation method, leveraging a proprietary nuclei isolation buffer together with mechanically-controlled cell wall disruption. Compared to traditional methods (Figure 2, Panel A), this workflow yielded nuclei samples with higher purity and lower background, demonstrated by flow cytometric separation revealing two robust peaks for vegetative and generative nuclei (Figure 2, Panel B).

Figure 2. KeyGene’s proprietary nuclei isolation procedure generates high-purity and low-background pollen nuclei samples better than traditional pollen nuclei isolation. Panel A. Flow cytometry plots showing background, yield, and purity of vegetative and generative nuclei isolated with traditional procedures. Panel B. Flow cytometry plots showing corresponding data for vegetative and generative nuclei isolated with KeyGene’s novel proprietary isolation method.

Following KeyGene’s nuclei isolation procedure to tobacco pollen, purified nuclei were prepared for the generation of a full-length RNA-seq library. This protocol integrates SMART (Switching Mechanism At 5′ end of RNA Template) technology with the ICELL8 cx Single-Cell System to achieve full-length transcriptome analysis with single-nuclei resolution. Nuclei suspensions were dispensed into 5,184 nanowells of the ICELL8 350v chip, and subsequent imaging with the ICELL cx system provided 1,701 single-nuclei candidates for full-length RNA-seq library preparation powered by the SMART-Seq Pro kit.

This high-throughput workflow resulted in the detection, on average, of approximately 9,000 genes per nucleus.

Leverage the outstanding sensitivity of the SMART-Seq Pro Application Kit to reveal novel nuclei populations with distinct gene expression profiles

The resulting snRNA-seq data was further analyzed at KeyGene using Seurat R, a highly scalable multimodal analysis package. A UMAP plot was generated based on the top 5,000 differentially expressed genes. In addition to distinct populations for generative and vegetative nuclei, the SMART-Seq Pro application kit identified a potentially novel population in an intermediate developmental or transitional state located on the periphery of each UMAP cluster (Figure 3, Panel A). These “transitional” nuclei displayed a similar gene expression profile to the corresponding nuclei type, but at an intermediate level of expression for various homologs of certain marker genes, such as L-ascorbate oxidase (Figure 3, Panel B).

Figure 3. Analysis and annotation with Seurat reveal different nuclei types. Panel A. UMAP plot showing tobacco pollen nuclei clusters based on differential gene expression. Red, generative nuclei; blue, vegetative nuclei; green, “transitional” nuclei. Panel B. Violin plots showing changes in the expression of four distinct L-ascorbate oxidase homologs across different nuclei types.

Takeaways

The integration of the KeyGene nuclei isolation procedures with the SMART-Seq Pro Application Kit on the ICELL8 cx system alleviates many of the obstacles that come with challenging pollen samples, providing a high-quality RNA-seq library at single-nuclei resolution. Rigorous analysis of these datasets can reveal critical insights into the RNA landscape of crop pollen that may provide new leads to improve agriculturally relevant crop traits related to pollen quality.

References

Underwood C.J. et al. A PARTHENOGENESIS allele from apomictic dandelion can induce egg cell division without fertilization in lettuce. Nature Genetics 2022 54(1), 84-93 (2022)

Dreissig S. et al. Sequencing of single pollen nuclei reveals meiotic recombination events at megabase resolution and circumvents segregation distortion caused by postmeiotic processes. Frontiers in Plant Science 8, 1620 (2017)

Sunaga-Franze D.Y. et al. Single-nucleus RNA sequencing of plant tissues using a nanowell-based system. The Plant Journal 108(3), 859-869 (2021)

Ichino L. Single-nucleus RNA-seq reveals that MBD5, MBD6, and SILENZIO maintain silencing in the vegetative cell of developing pollen. Cell Reports 41 (8), 111699 (2022).