Functional Insights from Single-Cell RNA Sequencing in Developing Maize Ears

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Summary

Within the maize ear's structural complexity, the potency of its meristems largely dictates crop yield. Historically, discerning the gamut of cellular variations and the intricate tapestry of gene networks influencing them was confined to morphological evaluations and classical genetics—a method plagued by the challenges of genetic redundancy and pleiotropy. By delving into the transcriptional nuances of 12,525 individual cells within the maize ear, this study has curated a detailed developmental atlas epitomized by single-cell RNA sequencing. This atlas, subjected to validation through mRNA in situ hybridization and fluorescence-activated cell sorting RNA-sequencing, stands as a beacon for future genetic exploration, proffering insight into genetic redundancy, weaving together transcriptional matrices, and spotlighting genes that potentially influence agricultural output.

Fig. 1 Graphical abstract¹.

Research Criteria

Through single-cell RNA sequencing (scRNA-seq), they were able to identify major cell types and developmental markers in maize ears. The study revealed gene co-expression networks that can predict genetic redundancy and highlight transcriptional regulatory networks. Furthermore, the integration of scRNA-seq with other techniques like ChIP-seq/ATAC-seq and GWAS helped in identifying candidate maize yield-associated genes. This research provides valuable insights into maize breeding by pinpointing potential trait-associated genes.

Sample Type

Maize ears

Result - Building a Single-Cell Transcriptome the Developing Maize Ear Atlas

In an intricate endeavor to construct a single-cell atlas of developing maize ears, researchers meticulously selected the 5–10 mm developmental stage, a pivotal juncture where cardinal developmental and architectural determinations transpire. They adeptly refined a cell wall digestion technique, cognizant of the unique composition of grass cell walls, facilitating the isolation of ear protoplasts in a mere 45 minutes. Despite the fragility of these protoplasts, the team adeptly filtered out cellular debris and subsequently sequenced scRNA-seq libraries using the Illumina platform, profiling an impressive 12,525 individual cells. Addressing the inherent technical challenges of scRNA-seq, they employed MetaNeighbor to discern reproducible cell clusters, culminating in the identification of 12 distinct meta-clusters. Notably, even though certain genes exhibited responsiveness to protoplasting, their impact on clustering was negligible, corroborating previous findings.

Fig. 2 Isolation of maize ear protoplasts for the development of a single-cell transcriptomic atlas¹.

Result - scRNA-seq Networks Predict Redundancy

In this research, the intricacies of gene redundancy in maize were explored using single-cell RNA sequencing (scRNA-seq) networks. The research underscored the challenge in distinguishing between superfluous and non-superfluous paralogs, as illustrated by the maize branching mutant known as ramosa3 (ra3) and its counterpart, ZmTREHALOSE PHOSPHATE PHOSPHATASE 4 (ZmTPP4). Notably, while ZmTPP4 and ZmTPP12 both showed upregulation in ra3 mutants, only ZmTPP4 exhibited high co-expression with RA3 in single-cell data. This suggests that scRNA-seq can more accurately predict functional redundancy than bulk tissue RNA-seq. Further investigation into the VASCULAR PLANT ONE-ZINC-FINGER (ZmVOZ) gene family supported this notion, revealing that ZmVOZ4 and ZmVOZ5 paralogs exhibited similar co-expression patterns, hinting at their redundant roles. The utility of scRNA-seq was further emphasized in its potential to construct transcriptional regulatory networks, as demonstrated by the co-expression of KN1 with its direct targets. The study's findings illuminate the potential of scRNA-seq in predicting genetic redundancy and aiding in the delineation of transcriptional regulatory pathways.

Fig. 3 Single-cell RNA sequencing (scRNA-seq) holds the potential to anticipate genetic redundancy while also contributing to the anticipation of intricate transcriptional regulatory networks¹.

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In the realm of cellular complexities, homogeneity remains a rarity among populations, as their traits synchronize infrequently. Our expertise lies in singular cell RNA sequencing, an endeavor to unveil the multifarious transcriptome within disparate specimens. Through comprehensive pipelines encompassing sample priming, library synthesis, and data interpretation, we optimize your venture's malleability, velocity, and precision, epitomizing the essence of Creative Biolabs' contributions.

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At Creative Biolabs, we proudly deliver unparalleled solutions in single-cell RNA sequencing for researchers and visionaries worldwide. Through the utilization of state-of-the-art methodologies and our profound mastery, we produce intricate and high-resolution scRNA-seq data. This empowers the investigation of genetic diversity and complexity at the cellular level, unraveling distinctive cell subsets alongside their distinctive gene expression patterns. Our adaptable protocols and holistic offerings cater to the distinct needs and budgetary considerations of our clients, solidifying our role as the favored partner in advancing scientific inquiry and achieving groundbreaking revelations.

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Reference

1. Xu, Xiaosa, et al. "Single-cell RNA sequencing of developing maize ears facilitates functional analysis and trait candidate gene discovery." Developmental cell 56.4 (2021): 557-568.