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Abstract Understanding the mechanisms underlying key agricultural traits remains a central challenge in crop research, but recent advances in technologies are providing powerful tools to address this issue. Among these, single-cell and spatial transcriptomics have revealed tissue heterogeneity and spatial organization, offering unique insights into cellular gene expression dynamics and the coordinated activity of multiple cell types. These approaches help uncover how specific cell types contribute to agricultural traits and refine candidate loci lists through integration with trait-associated loci. Additionally, single-cell and spatial transcriptomics have the potential to serve as cell-level readout platforms integrating cellular perturbations, enabling high-throughput discovery of causal relationships between genotype and gene expression at the cellular level in plants. Successful implementation will accelerate the identification of key genetic variants for crop improvement. Here we review lessons learned from application of single-cell screening in mammalian cells, highlight major technical and biological barriers to its use in plants, and outline potential strategies to overcome these challenges. Together, the widespread application and integration of single-cell and spatial transcriptomics with other technologies enable not only the descriptive cataloging of cell states but also the causal interrogation of sequence functions and regulatory networks at cell type resolution, ultimately advancing gene function studies and accelerating crop improvement. 

Abstract Gene duplication is a major source of evolutionary innovation, enabling the emergence of novel expression patterns and functions. Leveraging single-cell genomics, we investigated the transcriptional and cis-regulatory landscapes of duplicated genes in cultivated soybean (Glycine max), which has undergone 2 rounds of whole-genome duplication. Our analysis revealed extensive diversity of transcriptional profiles within and across tissues among duplicated gene pairs. Within-tissue divergence was largely attributable to genetic variation in their associated accessible chromatin regions (ACRs), where cis-regulatory elements reside, whereas cross-tissue divergence was more likely shaped by dynamics in ACR chromatin accessibility profiles across tissues. Distinct duplication mechanisms also likely give rise to different types of cis-regulatory variants, contributing variably to transcriptional divergence. By comparing ACRs associated with gene sets derived from 2 rounds of whole-genome duplication and sharing a common ancestral gene, we found that most ACRs retained one or multiple corresponding duplicated sequences in which mutations gradually accumulated over time, while a subset likely arose de novo. Finally, we traced the evolution of cell-type-specific expression and cell-type-specific ACRs within duplicated gene sets, illustrating a powerful framework for identifying candidate regulatory regions driving cell-type-specific expression. Collectively, our findings highlight the important role of cis-regulatory evolution in shaping transcriptional divergence in a spatiotemporal manner, uncovered with the resolution of single-cell genomics. 

Abstract Single-cell ATAC-seq has emerged as a powerful approach for revealing candidate cis-regulatory elements genome-wide at cell-type resolution. However, current single-cell methods suffer from limited throughput and high costs. Here, we present a novel technique called scifi-ATAC-seq, single-cell combinatorial fluidic indexing ATAC-sequencing, which combines a barcoded Tn5 pre-indexing step with droplet-based single-cell ATAC-seq using the 10X Genomics platform. With scifi-ATAC-seq, up to 200,000 nuclei across multiple samples can be indexed in a single emulsion reaction, representing an approximately 20-fold increase in throughput compared to the standard 10X Genomics workflow. 

Abstract Gene regulation in eukaryotes is partly shaped by the 3D organization of chromatin within the cell nucleus. Distal interactions between cis-regulatory elements and their target genes are widespread, and many causal loci underlying heritable agricultural traits have been mapped to distal non-coding elements. The biology underlying chromatin loop formation in plants is poorly understood. Dissecting the sequence features that mediate distal interactions is an important step toward identifying putative molecular mechanisms. Here, we trained GenomicLinks, a deep learning model, to identify DNA sequence features predictive of 3D chromatin interactions in maize. We found that the presence of binding motifs of specific transcription factor classes, especially bHLH, is predictive of chromatin interaction specificities. Using an in silico mutagenesis approach we show the removal of these motifs from loop anchors leads to reduced interaction probabilities. We were able to validate these predictions with single-cell co-accessibility data from different maize genotypes that harbor natural substitutions in these TF binding motifs. GenomicLinks is currently implemented as an open-source web tool, which should facilitate its wider use in the plant research community. 

Cis-regulatory elements are specific DNA sequences that control gene expression in a spatiotemporal manner, and variation within these elements represents a major source of phenotypic diversity and evolutionary innovation. Nevertheless, how regulatory elements evolve and shape gene expression remains poorly understood, particularly in plants. The well-resolved phylogeny of allopolyploid peanut (Arachis hypogaea) and its diploid progenitors,Arachis duranensisandArachis ipaensis, provides an ideal system to investigate the regulatory evolution at a lineage-specific level. By integrating comparative analyses of sequence similarity, chromatin accessibility, histone modifications, conserved noncoding sequences (CNSs), and gene expression, we reconstructed the evolutionary trajectories of Accessible Chromatin Regions (ACRs), where regulatory elements typically reside, and revealed their distinct contributions to homoeolog expression bias, unequal expressions between homoeologs. Most ACRs exhibited high sequence similarity, comparable chromatin accessibility, and conserved states for H3K4me3, H3K56ac, and H3K36me3, indicating regulatory stability after hybridization and polyploidization. However, a subset of novel ACRs emerged de novo from previously nonregulatory regions or through sequence mutations in preexisting ACRs, arising at different rates and evolutionary stages. Notably, even highly sequence-conserved ACRs exhibited substantial variation in chromatin accessibility, consistent with CNS composition differences and minor sequence variation, although causal relationships remain to be demonstrated. Our analyses further revealed a complex spectrum of CNS dynamics within the diploid-polyploid framework. Overall, our study provides empirical insights into the fine-scale evolution of plant regulatory landscapes and complements previous large-scale comparisons across distant lineages. 

Spatial transcriptomics is a disruptive technology that enables the identification of cell-type-specific transcripts en masse. However, the use of spatial transcriptomics for plant tissues has been challenging due to issues related to tissue preparation. Here, we present a protocol for preparing fresh frozen soybean tissues for spatial transcriptomics. We describe the steps for embedding, cryosectioning, fixation, staining, and imaging of soybean tissues.We then detail procedures for library preparation and sequencing. 

While considerable knowledge exists about the enzymes pivotal for C₄photosynthesis, much less is known about thecis-regulation important for specifying their expression in distinct cell types. Here, we use single-cell-indexed ATAC-seq to identify cell-type-specific accessible chromatin regions (ACRs) associated with C₄enzymes for five different grass species. This study spans four C₄species, covering three distinct photosynthetic subtypes:Zea maysandSorghum bicolor(NADP-dependent malic enzyme),Panicum miliaceum(NAD-dependent malic enzyme),Urochloa fusca(phosphoenolpyruvate carboxykinase), along with the C₃outgroupOryza sativa. We studied thecis-regulatory landscape of enzymes essential across all C₄species and those unique to C₄subtypes, measuring cell-type-specific biases for C₄enzymes using chromatin accessibility data. Integrating these data with phylogenetics revealed diverse co-option of gene family members between species, showcasing the various paths of C₄evolution. Besides promoter proximal ACRs, we found that, on average, C₄genes have two to three distal cell-type-specific ACRs, highlighting the complexity and divergent nature of C₄evolution. Examining the evolutionary history of these cell-type-specific ACRs revealed a spectrum of conserved and novel ACRs, even among closely related species, indicating ongoing evolution ofcis-regulation at these C₄loci. This study illuminates the dynamic and complex nature ofcis-regulatory elements evolution in C₄photosynthesis, particularly highlighting the intricatecis-regulatory evolution of key loci. Our findings offer a valuable resource for future investigations, potentially aiding in the optimization of C₃crop performance under changing climatic conditions.