Dissecting the molecular basis of spike traits by integrating gene regulatory network and genetic variation in wheat.

Spike architecture influences both grain weight and grain number per spike, which are the two major components of grain yield in bread wheat (Triticum aestivum L.). However, the complex wheat genome and the influence of various environmental factors pose challenges in mapping the causal genes affecting the spike traits. Here, we systematically identify genes involved in spike trait formation by integrating the information of genomic variation and gene regulatory network (GRN) controlling young spike development in wheat. We obtained 170 loci that are responsible for variations of spike length (SL), spikelet number per spike (SNS) and grain number per spike (GNS) through genome wide association study (GWAS) and meta-QTL analysis. The GRNs for young inflorescence at double ridge stage (DRS) and floret primordium stage (FPS) in which spikelet meristem and floret meristem are predominant, respectively, were constructed by integrating transcriptome, histone modifications, chromatin accessibility, eQTL, and protein-protein interactome. Strikingly, we identified 169 hub genes, whose polymorphisms are significantly associated with variation of spike trait from the network and they are located in 76 of the 170 QTL regions. In addition, the functions of TaZF-B1, VRT-B2 and TaSPL15-A/D in establishing wheat spike architecture were verified. The study provides valuable molecular resources to understand spike traits and the approach of combining genetic analysis and developmental regulatory network is robust to dissect complex trait.

Capture of regulatory factors via CRISPR-dCas9 for mechanistic analysis of fine-tuned SERRATE expression in Arabidopsis.

SERRATE (SE) plays an important role in many biological processes and under biotic stress resistance. However, little about the control of SE has been clarified. Here we present a method named native chromatin-associated proteome affinity by CRISPR-dCas9 (CASPA-dCas9) to holistically capture native regulators of the SE locus. Several key regulatory factors including PHYTOCHROME RAPIDLY REGULATED 2 (PAR2), WRKY DNA-binding protein 19 (WRKY19) and the MYB-family protein MYB27 of SE are identified. MYB27 recruits the long non-coding RNA-PRC2 (SEAIR-PRC2) complex for H3K27me3 deposition on exon 1 of SE and subsequently represses SE expression, while PAR2-MYB27 interaction inhibits both the binding of MYB27 on the SE promoter and the recruitment of SEAIR-PRC2 by MYB27. The interaction between PAR2 and MYB27 fine-tunes the SE expression level at different developmental stages. In addition, PAR2 and WRKY19 synergistically promote SE expression for pathogen resistance. Collectively, our results demonstrate an efficient method to capture key regulators of target genes and uncover the precise regulatory mechanism for SE.

scPlantDB: a comprehensive database for exploring cell types and markers of plant cell atlases.

Recent advancements in single-cell RNA sequencing (scRNA-seq) technology have enabled the comprehensive profiling of gene expression patterns at the single-cell level, offering unprecedented insights into cellular diversity and heterogeneity within plant tissues. In this study, we present a systematic approach to construct a plant single-cell database, scPlantDB, which is publicly available at https://biobigdata.nju.edu.cn/scplantdb. We integrated single-cell transcriptomic profiles from 67 high-quality datasets across 17 plant species, comprising approximately 2.5 million cells. The data underwent rigorous collection, manual curation, strict quality control and standardized processing from public databases. scPlantDB offers interactive visualization of gene expression at the single-cell level, facilitating the exploration of both single-dataset and multiple-dataset analyses. It enables systematic comparison and functional annotation of markers across diverse cell types and species while providing tools to identify and compare cell types based on these markers. In summary, scPlantDB serves as a comprehensive database for investigating cell types and markers within plant cell atlases. It is a valuable resource for the plant research community.

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 regulatory 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 demonstrated that the cell-type-specific expression of lncRNAs largely explains their tissue specificity. In addition, 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 database (scPLAD; https://biobigdata.nju.edu.cn/scPLAD/). Overall, this work demonstrates the power of integrative single-cell data analysis applied to plant lncRNA biology and provides fundamental insights into lncRNA expression specificity and associated gene regulation.

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, 30 474 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 triplication γ, 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 flower 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.

All-fiber laser system for all-optical 87Rb Bose Einstein condensate to space application.

In the development of the Cold Atom Physics Research Rack (CAPR) on board the Chinese Space Station, the laser system plays a critical role in preparing the all-optical 87 R b Bose-Einstein condensates (BECs). An all-fiber laser system has been developed for CAPR to provide the required optical fields for atom interaction and to maintain the beam pointing in long-term operation. The laser system integrates a 780 nm fiber laser system and an all-fiber optical control module for sub-Doppler cooling, as well as an all-fiber 1064 nm laser system for evaporative cooling. The high-power, single-frequency 780 nm lasers are achieved through rare-Earth doped fiber amplification, fiber frequency-doubling, and frequency stabilization technology. The all-fiber optical control module divides the output of the 780 nm laser system into 15 channels and regulates them for cooling, trapping, and probing atoms. Moreover, the power consistency of each pair of cooling beams is ensured by three power tracking modules, which is a prerequisite for maintaining stable MOT and molasses. A high-power, compact, controlled-flexible, and highly stable l064 nm all-fiber laser system employing two-stage ytterbium-doped fiber amplifier (YDFA) technology has been designed for evaporative cooling in the optical dipole trap (ODT). Finally, an all-optical 87 R b BEC is realized with this all-fiber laser system, which provides an alternative solution for trapping and manipulating ultra-cold atoms in challenging environmental conditions.

The ChIP-Hub Resource: Toward plantEncode.

Recent advances in sequencing technologies lead to the generation of an enormous amount of regulome and epigenome data in a variety of plant species. However, a comprehensive standardized resource is so far not available. In this chapter, we present ChIP-Hub, an integrative platform that has been developed based on the ENCODE standards by collecting and reanalyzing regulatory genomic datasets from 41 plant species. The ChIP-hub website is introduced in this chapter, including information on detailed steps of searching, data download, and online analyses, which facilitates users to explore ChIP-Hub. We also provide a cross-species comparison of chromatin accessibility information that gives a thorough view of evolutionary regulatory networks in plants.

Single cell transcriptomic analyses implicate an immunosuppressive tumor microenvironment in pancreatic cancer liver metastasis.

Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic disease refractory to all targeted and immune therapies. However, our understanding of PDAC microenvironment especially the metastatic microenvironment is very limited partly due to the inaccessibility to metastatic tumor tissues. Here, we present the single-cell transcriptomic landscape of synchronously resected PDAC primary tumors and matched liver metastases. We perform comparative analysis on both cellular composition and functional phenotype between primary and metastatic tumors. Tumor cells exhibit distinct transcriptomic profile in liver metastasis with clearly defined evolutionary routes from cancer cells in primary tumor. We also identify specific subtypes of stromal and immune cells critical to the formation of the pro-tumor microenvironment in metastatic lesions, including RGS5+ cancer-associated fibroblasts, CCL18+ lipid-associated macrophages, S100A8+ neutrophils and FOXP3+ regulatory T cells. Cellular interactome analysis further reveals that the lack of tumor-immune cell interaction in metastatic tissues contributes to the formation of the immunosuppressive microenvironment. Our study provides a comprehensive characterization of the transcriptional landscape of PDAC liver metastasis.

A Linearly Polarized Wavelength-Tunable Q-Switched Fiber Laser with a Narrow Spectral Bandwidth of 112 MHz.

A tunable and narrow-bandwidth Q-switched ytterbium-doped fiber (YDF) laser is investigated in this paper. The non-pumped YDF acts as a saturable absorber and, together with a Sagnac loop mirror, provides a dynamic spectral-filtering grating to achieve a narrow-linewidth Q-switched output. By adjusting an etalon-based tunable fiber filter, a tunable wavelength from 1027 nm to 1033 nm is obtained. When the pump power is 1.75 W, the Q-switched laser pulses with a pulse energy of 10.45 nJ, and a repetition frequency of 11.98 kHz and spectral linewidth of 112 MHz are obtained. This work paves the way for the generation narrow-linewidth Q-switched lasers with tunable wavelengths in conventional ytterbium, erbium, and thulium fiber bands to address critical applications such as coherent detection, biomedicine, and nonlinear frequency conversion.

Efficient single-frequency 972†nm Yb-doped fiber amplifier with core pumping and elevated temperature.

In this work, we present a monolithic single-frequency, single-mode and polarization maintaining Yb-doped fiber (YDF) amplifier delivering up to 6.9 W at 972 nm with a high efficiency of 53.6%. Core pumping at 915 nm and elevated temperature of 300 °C were applied to suppress the unwanted 977 nm and 1030 nm ASE in YDF, so as to improve the 972 nm laser efficiency. In addition, the amplifier was further used to generate a single-frequency 486 nm blue laser with 590 mW of output power by single-pass frequency doubling.

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 transcriptomic 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 present scPlant, a versatile framework for exploring plant single-cell atlases with minimum input 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, trajectory inference, cross-species data integration, and cell-type-specific gene regulatory network construction. In addition, a variety of visualization tools are bundled in a built-in Shiny application, enabling exploration of single-cell transcriptomic data on the fly.

Asymmetric gene expression and cell-type-specific regulatory networks in the root of bread wheat revealed by single-cell multiomics analysis.

BACKGROUND: Homoeologs are defined as homologous genes resulting from allopolyploidy. Bread wheat, Triticum aestivum, is an allohexaploid species with many homoeologs. Homoeolog expression bias, referring to the relative contribution of homoeologs to the transcriptome, is critical for determining the traits that influence wheat growth and development. Asymmetric transcription of homoeologs has been so far investigated in a tissue or organ-specific manner, which could be misleading due to a mixture of cell types. RESULTS: Here, we perform single nuclei RNA sequencing and ATAC sequencing of wheat root to study the asymmetric gene transcription, reconstruct cell differentiation trajectories and cell-type-specific gene regulatory networks. We identify 22 cell types. We then reconstruct cell differentiation trajectories that suggest different origins between epidermis/cortex and endodermis, distinguishing bread wheat from Arabidopsis. We show that the ratio of asymmetrically transcribed triads varies greatly when analyzing at the single-cell level. Hub transcription factors determining cell type identity are also identified. In particular, we demonstrate that TaSPL14 participates in vasculature development by regulating the expression of BAM1. Combining single-cell transcription and chromatin accessibility data, we construct the pseudo-time regulatory network driving root hair differentiation. We find MYB3R4, REF6, HDG1, and GATAs as key regulators in this process. CONCLUSIONS: Our findings reveal the transcriptional landscape of root organization and asymmetric gene transcription at single-cell resolution in polyploid wheat.

TripletCell: a deep metric learning framework for accurate annotation of cell types at the single-cell level.

Single-cell RNA sequencing (scRNA-seq) has significantly accelerated the experimental characterization of distinct cell lineages and types in complex tissues and organisms. Cell-type annotation is of great importance in most of the scRNA-seq analysis pipelines. However, manual cell-type annotation heavily relies on the quality of scRNA-seq data and marker genes, and therefore can be laborious and time-consuming. Furthermore, the heterogeneity of scRNA-seq datasets poses another challenge for accurate cell-type annotation, such as the batch effect induced by different scRNA-seq protocols and samples. To overcome these limitations, here we propose a novel pipeline, termed TripletCell, for cross-species, cross-protocol and cross-sample cell-type annotation. We developed a cell embedding and dimension-reduction module for the feature extraction (FE) in TripletCell, namely TripletCell-FE, to leverage the deep metric learning-based algorithm for the relationships between the reference gene expression matrix and the query cells. Our experimental studies on 21 datasets (covering nine scRNA-seq protocols, two species and three tissues) demonstrate that TripletCell outperformed state-of-the-art approaches for cell-type annotation. More importantly, regardless of protocols or species, TripletCell can deliver outstanding and robust performance in annotating different types of cells. TripletCell is freely available at https://github.com/liuyan3056/TripletCell. We believe that TripletCell is a reliable computational tool for accurately annotating various cell types using scRNA-seq data and will be instrumental in assisting the generation of novel biological hypotheses in cell biology.

Lipid-accumulated reactive astrocytes promote disease progression in epilepsy.

Reactive astrocytes play an important role in neurological diseases, but their molecular and functional phenotypes in epilepsy are unclear. Here, we show that in patients with temporal lobe epilepsy (TLE) and mouse models of epilepsy, excessive lipid accumulation in astrocytes leads to the formation of lipid-accumulated reactive astrocytes (LARAs), a new reactive astrocyte subtype characterized by elevated APOE expression. Genetic knockout of APOE inhibited LARA formation and seizure activities in epileptic mice. Single-nucleus RNA sequencing in TLE patients confirmed the existence of a LARA subpopulation with a distinct molecular signature. Functional studies in epilepsy mouse models and human brain slices showed that LARAs promote neuronal hyperactivity and disease progression. Targeting LARAs by intervention with lipid transport and metabolism could thus provide new therapeutic options for drug-resistant TLE.

The SMARCA4R1157W mutation facilitates chromatin remodeling and confers PRMT1/SMARCA4 inhibitors sensitivity in colorectal cancer.

Genomic studies have demonstrated a high frequency of genetic alterations in components of the SWI/SNF complex including the core subunit SMARCA4. However, the mechanisms of tumorigenesis driven by SMARCA4 mutations, particularly in colorectal cancer (CRC), remain largely unknown. In this study, we identified a specific, hotspot mutation in SMARCA4 (c. 3721C>T) which results in a conversion from arginine to tryptophan at residue 1157 (R1157W) in human CRC tissues associated with higher-grade tumors and controls CRC progression. Mechanistically, we found that the SMARCA4R1157W mutation facilitated its recruitment to PRMT1-mediated H4R3me2a (asymmetric dimethylation of Arg 3 in histone H4) and enhanced the ATPase activity of SWI/SNF complex to remodel chromatin in CRC cells. We further showed that the SMARCA4R1157W mutant reinforced the transcriptional expression of EGFR and TNS4 to promote the proliferation of CRC cells and patient-derived tumor organoids. Importantly, we demonstrated that SMARCA4R1157W CRC cells and mutant cell-derived xenografts were more sensitive to the combined inhibition of PRMT1 and SMARCA4 which act synergistically to suppress cell proliferation. Together, our findings show that SMARCA4-R1157W is a critical activating mutation, which accelerates CRC progression through facilitating chromatin recruitment and remodeling. Our results suggest a potential precision therapeutic strategy for the treatment of CRC patients carrying the SMARCA4R1157W mutation.

An antisense intragenic lncRNA SEAIRa mediates transcriptional and epigenetic repression of SERRATE in Arabidopsis.

SERRATE (SE) is a core protein for microRNA (miRNA) biogenesis as well as for mRNA alternative splicing. Investigating the regulatory mechanism of SE expression is hence critical to understanding its detailed function in diverse biological processes. However, little about the control of SE expression has been clarified, especially through long noncoding RNA (lncRNA). Here, we identified an antisense intragenic lncRNA transcribed from the 3' end of SE, named SEAIRa. SEAIRa repressed SE expression, which in turn led to serrated leaves. SEAIRa recruited plant U-box proteins PUB25/26 with unreported RNA binding ability and a ubiquitin-like protein related to ubiquitin 1 (RUB1) for H2A monoubiquitination (H2Aub) at exon 11 of SE. In addition, PUB25/26 helped cleave SEAIRa and release the 5' domain fragment, which recruited the PRC2 complex for H3 lysine 27 trimethylation (H3K27me3) deposition at the first exon of SE. The distinct modifications of H2Aub and H3K27me3 at different sites of the SE locus cooperatively suppressed SE expression. Collectively, our results uncover an epigenetic mechanism mediated by the lncRNA SEAIRa that modulates SE expression, which is indispensable for plant growth and development.

An Investigation of All Fiber Free-Running Dual-Comb Spectroscopy.

A dual-comb spectroscopy (DCS) system uses two phase-locked optical frequency combs with a slight difference in the repetition frequency. The spectrum can be sampled in the optical frequency (OF) domain and reproduces the characteristics in the radio frequency (RF) domain through asynchronous optical sampling. Therefore, the DCS system shows great advantages in achieving precision spectral measurement. During application, the question of how to reserve the mutual coherence between the two combs is the key issue affecting the application of the DCS system. This paper focuses on a software algorithm used to realize the mutual coherence of the two combs. Therefore, a pair of free-running large anomalous dispersion fiber combs, with a center wavelength of approximately 1064 nm, was used. After the signal process, the absorption spectra of multiple species were simultaneously obtained (simulated using the reflective spectra of narrow-bandwidth fiber Bragg gratings, abbreviated as FBG). The signal-to-noise ratio (SNR) could reach 13.97 dB (25) during the 100 ms sampling time. In this study, the feasibility of the system was first verified through the simulation system; then, a principal demonstration experiment was successfully executed. The whole system was connected by the optical fiber without additional phase-locking equipment, showing promise as a potential solution for the low-cost and practical application of DCS systems.

Mapping open chromatin by ATAC-seq in bread wheat.

Gene transcription is largely regulated by cis-regulatory elements. Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) is an emerging technology that can accurately map cis-regulatory elements in animals and plants. However, the presence of cell walls and chloroplasts in plants hinders the extraction of high-quality nuclei, thereby affects the quality of ATAC-seq data. Meanwhile, it is tricky to perform ATAC-seq with different tissue types, especially for those with limited size and amount. Moreover, with rapid growth of ATAC-seq datasets from plants, powerful and easy-to-use data analysis pipelines for ATAC-seq, especially for wheat is lacking. Here, we provided an all-in-one solution for mapping open chromatin in wheat including both experimental and data analysis procedure. We efficiently obtained nuclei with less cell debris from various wheat tissues. High-quality ATAC-seq data from young spike and ovary, which are hard to harvest were generated. We determined that the saturation sequencing depth of wheat ATAC-seq is about 16 Gb. Particularly, we developed a powerful and easy-to-use online pipeline to analyze the wheat ATAC-seq data and this pipeline can be easily extended to other plant species. The method developed here will facilitate plant regulatory genome study not only for wheat but also for other plant species.

Line shape of a delayed self-heterodyne varied with noise types and delays.

The delayed self-heterodyne and self-homodyne (DSH) method is widely used for measuring the line shapes of high coherent lasers. This method results in an autocorrelation of a laser line under the condition of a delay that is much larger than its coherent time. In practice, the delay is often not so long, especially for very narrow linewidth lasers, resulting in errors in rebuilding the laser's line shape from the DSH line. Many papers were devoted to the topic, but most of them are based on the formula for white noise. Analytical formulas of phase variance for 1/f noises are presented in this paper; the DSH line shapes for different noise types and different delay lengths are simulated based on the formulas. Some experimental data of the DSH line, combined with the power spectral density of frequency noise, are processed, showing good agreement with the theoretical analysis. It is indicated that the DSH line shape shows complicated behaviors varied with the delay, with noise types, and with the measurement duration. Such effects are to be compensated for in retrieving the laser's linewidth from the DSH data.

Exploring long non-coding RNA networks from single cell omics data.

Single-cell omics technologies provide an unprecedented opportunity to decipher molecular mechanisms underlying various biological processes in a cellular heterogeneity manner. The emergence of such techniques promotes the exploration of lncRNAs, which are known to be tissue- and cell-specific noncoding transcripts involving the regulation of multiple important cellular processes. In this review, we introduce the advancement of lncRNA studies which benefit from single-cell omics data analysis. We discuss the expression heterogeneity of lncRNAs, their cell-type specificity and associated gene regulatory networks (GRNs) from a single-cell perspective. We also summarized the state-of-the-art single-cell omics resources and tools for the construction of single-cell GRNs (scGRNs) that could be potentially used for lncRNA functional study. Finally, we highlight the challenges and prospective for scGRN exploration in lncRNA biology.