Comprehensive integration of single-cell transcriptomic data illuminates the regulatory network architecture of plant cell fate specification

Plant morphogenesis relies on precise gene expression programs at the proper time and position which is orchestrated by transcription factors(TFs)in intricate regulatory networks in a cell-type specific manner.Here we introduced a comprehensive single-cell transcriptomic atlas of Arabidopsis seedlings.This atlas is the result of meticulous integration of 63 previously published scRNA-seq datasets,addressing batch effects and conserving biological variance.This integration spans a broad spectrum of tissues,including both below-and above-ground parts.Utilizing a rigorous approach for cell type annotation,we identified 47 distinct cell types or states,largely expanding our current view of plant cell compositions.We systematically constructed cell-type specific gene regulatory networks and uncovered key regulators that act in a coordinated manner to control cell-type specific gene expression.Taken together,our study not only offers extensive plant cell atlas exploration that serves as a valuable resource,but also provides molecular insights into gene-regulatory programs that varies from different cell types.

A chromosome-level genome assembly provides insights into Cornus wilsoniana evolution, oil biosynthesis, and floral bud development

Cornus wilsoniana W.is a woody oil plant with high oil content and strong hypolipidemic effects,making it a valuable species for medicinal,landscaping,and ecological purposes in China.To advance genetic research on this species,we employed PacBio together with Hi-C data to create a draft genome assembly for C.wilsoniana.Based on an 11-chromosome anchored chromosome-level assembly,the estimated genome size was determined to be 843.51 Mb.The N50 contig size and N50 scaffold size were calculated to be 4.49 and 78.00 Mb,respectively.Furthermore,30474 protein-coding genes were annotated.Comparative genomics analysis revealed that C.wilsoniana diverged from its closest species∼12.46 million years ago(Mya).Furthermore,the divergence between Cornaceae and Nyssaceae occurred>62.22 Mya.We also found evidence of whole-genome duplication events and whole-genome triplicationγ,occurring at∼44.90 and 115.86 Mya.We further inferred the origins of chromosomes,which sheds light on the complex evolutionary history of the karyotype of C.wilsoniana.Through transcriptional and metabolic analysis,we identified two FAD2 homologous genes that may play a crucial role in controlling the oleic to linoleic acid ratio.We further investigated the correlation between metabolites and genes and identified 33 MADS-TF homologous genes that may affect f lower morphology in C.wilsoniana.Overall,this study lays the groundwork for future research aimed at identifying the genetic basis of crucial traits in C.wilsoniana.

Single-cell transcriptome analysis dissects lncRNA-associated gene networks in Arabidopsis

The plant genome produces an extremely large collection of long noncoding RNAs(lncRNAs)that are generally expressed in a context-specific manner and have pivotal roles in regulation of diverse biological processes.Here,we mapped the transcriptional heterogeneity of lncRNAs and their associated gene reg-ulatory networks at single-cell resolution.We generated a comprehensive cell atlas at the whole-organism level by integrative analysis of 28 published single-cell RNA sequencing(scRNA-seq)datasets from juvenile Arabidopsis seedlings.We then provided an in-depth analysis of cell-type-related lncRNA signatures that show expression patterns consistent with canonical protein-coding gene markers.We further demon-strated that the cell-type-specific expression of lncRNAs largely explains their tissue specificity.In addi-tion,we predicted gene regulatory networks on the basis of motif enrichment and co-expression analysis of lncRNAs and mRNAs,and we identified putative transcription factors orchestrating cell-type-specific expression of lncRNAs.The analysis results are available at the single-cell-based plant lncRNA atlas data-base(scPLAD;https://biobigdata.nju.edu.cn/scPLAD/).Overall,this work demonstrates the power of inte-grative single-cell data analysis applied to plant lncRNA biology and provides fundamental insights into lncRNA expression specificity and associated gene regulation.

scPlant:A versatile framework for single-cell transcriptomic data analysis in plants

Single-cell transcriptomics has been fully embraced in plant biological research and is revolutionizing our understanding of plant growth,development,and responses to external stimuli.However,single-cell tran-scriptomic data analysis in plants is not trivial,given that there is currently no end-to-end solution and that integration of various bioinformatics tools involves a large number of required dependencies.Here,we pre-sent scPlant,a versatile framework for exploring plant single-cell atlases with minimuminput data provided by users.The scPlant pipeline is implemented with numerous functions for diverse analytical tasks,ranging from basic data processing to advanced demands such as cell-type annotation and deconvolution,trajec-tory inference,cross-species data integration,and cell-type-specific gene regulatory network construc-tion.In addition,a variety of visualization tools are bundled in a built-in Shiny application,enabling explo-ration of single-cell transcriptomic data on the fly.

Modelling-based evaluation of the effect of quarantine control by the Chinese government in the coronavirus disease 2019 outbreak

Dear Editor,The recent outbreak of novel coronavirus disease 2019(COVID-19)has already become a global-scale epidemic.Since the case from China was reported on Dec 30th,2019(Huang et al.,2020;Li et al.,2020),the pathogen was soon identified as a new coronavirus on Jan 7th.

Systematic annotation of conservation states provides insights into regulatory regions in rice

Plant genomes contain a large fraction of noncoding sequences.The discovery and annotation of conserved noncoding sequences(CNSs)in plants is an ongoing challenge.Here we report the application of comparative genomics to systematically identify CNSs in 50 well-annotated Gramineae genomes using rice(Oryza sativa)as the reference.We conduct multiple-way whole-genome alignments to the rice genome.The rice genome is annotated as 20 conservation states(CSs)at single-nucleotide resolution using a multivariate hidden Markov model(Cons HMM)based on the multiple-genome alignments.Different states show distinct enrichments for various genomic features,and the conservation scores of CSs are highly correlated with the level of associated chromatin accessibility.We find that at least 33.5%of the rice genome is highly under selection,with more than 70%of the sequence lying outside of coding regions.A catalog of 855,366 regulatory CNSs is generated,and they significantly overlapped with putative active regulatory elements such as promoters,enhancers,and transcription factor binding sites.Collectively,our study provides a resource for elucidating functional noncoding regions of the rice genome and an evolutionary aspect of regulatory sequences in higher plants.