Search for: All records

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. 

Abstract Accurate genome annotations are essential to modern biology; however, they remain challenging to produce. Variation in gene structure and expression across species, as well as within an organism, make correctly annotating genes arduous; an issue exacerbated by pitfalls in current in silico methods. These issues necessitate complementary approaches to add additional confidence and rectify potential misannotations. Integration of epigenomic data into genome annotation is one such approach. In this study, we utilized sets of histone modification data, which are precisely distributed at either gene bodies or promoters to evaluate the annotation of the Zea mays genome. We leveraged these data genome wide, allowing for identification of annotations discordant with empirical data. In total, 13,159 annotation discrepancies were found in Z. mays upon integrating data across three different tissues, which were corroborated using RNA-based approaches. Upon correction, genes were extended by an average of 2128 base pairs, and we identified 2529 novel genes. Application of this method to five additional plant genomes identified a series of misannotations, as well as identified novel genes, including 13,836 in Asparagus officinalis, 2724 in Setaria viridis, 2446 in Sorghum bicolor, 8631 in Glycine max, and 2585 in Phaseolous vulgaris. This study demonstrates that histone modification data can be leveraged to rapidly improve current genome annotations across diverse plant lineages. 

SUMMARY Cis‐regulatory elements (CREs) are important sequences for gene expression and for plant biological processes such as development, evolution, domestication, and stress response. However, studying CREs in plant genomes has been challenging. The totipotent nature of plant cells, coupled with the inability to maintain plant cell types in culture and the inherent technical challenges posed by the cell wall has limited our understanding of how plant cell types acquire and maintain their identities and respond to the environment via CRE usage. Advances in single‐cell epigenomics have revolutionized the field of identifying cell‐type‐specific CREs. These new technologies have the potential to significantly advance our understanding of plant CRE biology, and shed light on how the regulatory genome gives rise to diverse plant phenomena. However, there are significant biological and computational challenges associated with analyzing single‐cell epigenomic datasets. In this review, we discuss the historical and foundational underpinnings of plant single‐cell research, challenges, and common pitfalls in the analysis of plant single‐cell epigenomic data, and highlight biological challenges unique to plants. Additionally, we discuss how the application of single‐cell epigenomic data in various contexts stands to transform our understanding of the importance of CREs in plant genomes.