Latent periodic process inference from single-cell RNA-seq data

AbstractConvoluted biological processes underlie the development of multicellular organisms and diseases. Advances in scRNA-seq make it possible to study these processes from cells at various developmental stages. Achieving accurate characterization is challenging, however, particularly for periodic processes, such as cell cycles. To address this, we developed Cyclum, a novel AutoEncoder approach that characterizes circular trajectories in the high-dimensional gene expression space. Cyclum substantially improves the accuracy and robustness of cell-cycle characterization beyond existing approaches. Applying Cyclum to removing cell-cycle effects leads to substantially improved delineations of cell subpopulations, which is useful for establishing various cell atlases and studying tumor heterogeneity. Cyclum is available at https://github.com/KChen-lab/cyclum.

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Genome-Wide Identification and Analysis of Cell Cycle Genes in Birch

Forests ◽

10.3390/f13010120 ◽

2022 ◽

Vol 13 (1) ◽

pp. 120

Author(s):

Yijie Li ◽

Song Chen ◽

Yuhang Liu ◽

Haijiao Huang

Keyword(s):

Cell Cycle ◽

Growth And Development ◽

Betula Pendula ◽

Cell Cycle Gene ◽

Expression Data ◽

Rna Seq ◽

Specific Expression ◽

Cell Cycles ◽

Cell Cycle Genes ◽

Genome Wide

Research Highlights: This study identified the cell cycle genes in birch that likely play important roles during the plant’s growth and development. This analysis provides a basis for understanding the regulatory mechanism of various cell cycles in Betula pendula Roth. Background and Objectives: The cell cycle factors not only influence cell cycles progression together, but also regulate accretion, division, and differentiation of cells, and then regulate growth and development of the plant. In this study, we identified the putative cell cycle genes in the B. pendula genome, based on the annotated cell cycle genes in Arabidopsis thaliana (L.) Heynh. It can be used as a basis for further functional research. Materials and Methods: RNA-seq technology was used to determine the transcription abundance of all cell cycle genes in xylem, roots, leaves, and floral tissues. Results: We identified 59 cell cycle gene models in the genome of B. pendula, with 17 highly expression genes among them. These genes were BpCDKA.1, BpCDKB1.1, BpCDKB2.1, BpCKS1.2, BpCYCB1.1, BpCYCB1.2, BpCYCB2.1, BpCYCD3.1, BpCYCD3.5, BpDEL1, BpDpa2, BpE2Fa, BpE2Fb, BpKRP1, BpKRP2, BpRb1, and BpWEE1. Conclusions: By combining phylogenetic analysis and tissue-specific expression data, we identified 17 core cell cycle genes in the Betulapendula genome.

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The evaluation of proliferation ability of cardiomyocytes in heart failure

E3S Web of Conferences ◽

10.1051/e3sconf/202127103064 ◽

2021 ◽

Vol 271 ◽

pp. 03064

Author(s):

Mengzi Gao

Keyword(s):

Heart Failure ◽

Cell Cycle ◽

Myocardial Dysfunction ◽

Left Ventricular ◽

Clinical Syndrome ◽

Rna Seq ◽

Cell Cycles ◽

A Cell ◽

Proliferation Ability ◽

Heat Failure

The proliferation ability of cardiomyocytes is always under a controversial situation, especially under some stress condition such as heart failure disease and external damages. Heat failure (HF) is a complex clinical syndrome that results from left ventricular myocardial dysfunction and contributes to dyspnea, fatigue and fluid retention. The proliferation ability is related to the cell cycles and lot of cell-cycle related genes are involved in the evaluation of proliferation ability of cardiomyocytes. RNA-seq is a quite common technique in evaluate the transcription expression pattern of genes in many studies. Here in our article we analyzed the existing RNA-seq dataset to evaluate the mRNA expression level of several genes which can be indicators of the activity of cell cycles. We found that the cyclin D2 which is a cell cycle activator is upregulated in dilated cardiomyopathy (DCM) disease, indicating that the proliferation ability may be higher in DCM heart. The results throw light on the proliferation research of adult cardiomyocytes.

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GhGPAT12/25 Are Essential for the Formation of Anther Cuticle and Pollen Exine in Cotton (Gossypium hirsutum L.)

Frontiers in Plant Science ◽

10.3389/fpls.2021.667739 ◽

2021 ◽

Vol 12 ◽

Author(s):

Meng Zhang ◽

Hengling Wei ◽

Pengbo Hao ◽

Aimin Wu ◽

Qiang Ma ◽

...

Keyword(s):

Developmental Stages ◽

Regulatory Mechanism ◽

Anther Development ◽

Biological Processes ◽

Rna Seq ◽

Loss Of Function ◽

Virus Induced Gene Silencing ◽

Cuticular Waxes ◽

Pollen Exine ◽

Anther Cuticle

Glycerol-3-phosphate acyltransferases (GPATs), critical for multiple biological processes like male fertility, have been extensively characterized. However, their precise functions and underlying regulatory mechanism in cotton anther development are unclear. This research demonstrated the importance of GhGPAT12/25 (a paralogs pair on A12/D12 sub-chromosome of cotton) to regulate the degradation of tapetum, anther cuticle formation, and pollen exine development. GhGPAT12 and GhGPAT25 exhibited specifically detected transcripts in tapetum and pollen exine during the early anther developmental stages. GhGPAT12/25 are sn-2 glycerol-3-phosphate acyltransferases and can transfer the acyl group of palmitoyl-CoA to glycerol-3-phosphate (G3P). CRISPR/Cas9-mediated knockout identified the functional redundancy of GhGPAT12 and GhGPAT25. Knockout of both genes caused completely male sterility associated with abnormal anther cuticle, swollen tapetum, and inviable microspores with defective exine and irregular unrestricted shape. RNA-seq analysis showed that the loss of function of GhGPAT12/25 affects the processes of wax metabolic, glycerol monomer biosynthesis, and transport. Consistently, cuticular waxes were dramatically reduced in mutant anthers. Yeast one-hybrid system (Y1H), virus-induced gene silencing (VIGS), and dual-luciferase (LUC) assays illustrated that GhMYB80s are likely to directly activate the expression of GhGPAT12/25. This study provides important insights for revealing the regulatory mechanism underlying anther development in cotton.

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Gene regulation inference from single-cell RNA-seq data with linear differential equations and velocity inference

10.1101/464479 ◽

2018 ◽

Cited By ~ 4

Author(s):

Pierre-Cyril Aubin-Frankowski ◽

Jean-Philippe Vert

Keyword(s):

Gene Regulation ◽

Single Cell ◽

De Novo ◽

State Of The Art ◽

Real Data ◽

Biological Processes ◽

Rna Seq ◽

Cell Cycles ◽

Linear Differential ◽

Cell Trajectories

AbstractSingle-cell RNA sequencing (scRNA-seq) offers new possibilities to infer gene regulation networks (GRN) for biological processes involving a notion of time, such as cell differentiation or cell cycles. It also raises many challenges due to the destructive measurements inherent to the technology. In this work we propose a new method named GRISLI for de novo GRN inference from scRNA-seq data. GRISLI infers a velocity vector field in the space of scRNA-seq data from profiles of individual data, and models the dynamics of cell trajectories with a linear ordinary differential equation to reconstruct the underlying GRN with a sparse regression procedure. We show on real data that GRISLI outperforms a recently proposed state-of-the-art method for GRN reconstruction from scRNA-seq data.

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RiceLncPedia: a comprehensive database of rice long non-coding RNAs

10.1101/2020.05.22.110569 ◽

2020 ◽

Author(s):

Zhengfeng Zhang ◽

Yao Xu ◽

Fei Yang ◽

Benze Xiao ◽

Guoliang Li

Keyword(s):

Experimental Validation ◽

Developmental Stages ◽

Data Sets ◽

Omics Data ◽

Biological Processes ◽

Rna Seq ◽

Current Version ◽

Non Coding Rnas ◽

Systematic Identification ◽

Different Tissues

ABSTRACTLong non-coding RNAs (lncRNAs) play significant functions in various biological processes including differentiation, development and adaptation to different environments. Although multi research focused on lncRNAs in rice, the systematic identification and annotation of lncRNAs expressed in different tissues, developmental stages under diverse conditions are still scarce. This impacts the elucidation of their functional significance and the further research on them. Here, RiceLncPedia (http://218.199.68.191:10092/) is constructed including rice lncRNAs explored from 2313 publically available rice RNA-seq libraries and characterize them with multi-omics data sets. In the current version, RiceLncPedia shows 6978 lncRNAs with abundant features: (i) expression profile across 2313 rice RNA-seq libraries; (ii) an online genome browser for rice lncRNAs; (iii) genome SNPs in lncRNA transcripts; (iv) lncRNA associations with phenotype; (v) overlap of lncRNAs with transposons; and (vi) LncRNA-miRNA interactions and lncRNAs as the precursors of miRNAs. In total, RiceLncPedia imported numerous of rice lncRNAs during development under various environments as well as their features extracted from multi-omics data and thus serve as a fruitful resource for rice-related research communities. RiceLncPedia will be further updated with experimental validation, functions association and epigenetic characteristics to greatly facilitate future investigation on rice lncRNAs.

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Gene regulation inference from single-cell RNA-seq data with linear differential equations and velocity inference

Bioinformatics ◽

10.1093/bioinformatics/btaa576 ◽

2020 ◽

Vol 36 (18) ◽

pp. 4774-4780 ◽

Cited By ~ 2

Author(s):

Pierre-Cyril Aubin-Frankowski ◽

Jean-Philippe Vert

Keyword(s):

Single Cell ◽

De Novo ◽

Real Data ◽

Supplementary Information ◽

Biological Processes ◽

Rna Seq ◽

Cell Cycles ◽

Gene Regulatory ◽

Linear Differential ◽

Cell Trajectories

Abstract Motivation Single-cell RNA sequencing (scRNA-seq) offers new possibilities to infer gene regulatory network (GRNs) for biological processes involving a notion of time, such as cell differentiation or cell cycles. It also raises many challenges due to the destructive measurements inherent to the technology. Results In this work, we propose a new method named GRISLI for de novo GRN inference from scRNA-seq data. GRISLI infers a velocity vector field in the space of scRNA-seq data from profiles of individual cells, and models the dynamics of cell trajectories with a linear ordinary differential equation to reconstruct the underlying GRN with a sparse regression procedure. We show on real data that GRISLI outperforms a recently proposed state-of-the-art method for GRN reconstruction from scRNA-seq data. Availability and implementation The MATLAB code of GRISLI is available at: https://github.com/PCAubin/GRISLI. Supplementary information Supplementary data are available at Bioinformatics online.

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Cluster analysis of Plasmodium RNA-seq time-course data identifies stage-specific co-regulated biological processes and regulatory elements

F1000Research ◽

10.12688/f1000research.9093.1 ◽

2016 ◽

Vol 5 ◽

pp. 1932 ◽

Cited By ~ 1

Author(s):

Efejiro Ashano ◽

Itunuoluwa Isewon ◽

Jelili Oyelade ◽

Ezekiel Adebiyi

Keyword(s):

Time Course ◽

Developmental Stages ◽

Regulatory Elements ◽

Development Stage ◽

Functional Enrichment ◽

Developmental Cycle ◽

Significant Activity ◽

Biological Processes ◽

Rna Seq ◽

Time Course Data

In this study, we interpreted RNA-seq time-course data of three developmental stages of Plasmodium species by clustering genes based on similarities in their expression profile without prior knowledge of the gene function. Functional enrichment of clusters of upregulated genes at specific time-points reveals potential targetable biological processes with information on their timings. We identified common consensus sequences that these clusters shared as potential points of coordinated transcriptional control. Five cluster groups showed upregulated profile patterns of biological interest. This included two clusters from the Intraerythrocytic Developmental Cycle (cluster 4 = 16 genes, and cluster 9 = 32 genes), one from the sexual development stage (cluster 2 = 851 genes), and two from the gamete-fertilization stage in the mosquito host (cluster 4 = 153 genes, and cluster 9 = 258 genes). The IDC expressed the least numbers of genes with only 1448 genes showing any significant activity of the 5020 genes (~29%) in the experiment. Gene ontology (GO) enrichment analysis of these clusters revealed a total of 671 uncharacterized genes implicated in 14 biological processes and components associated with these stages, some of which are currently being investigated as drug targets in on-going research. Five putative transcription regulatory binding motifs shared by members of each cluster were also identified, one of which was also identified in a previous study by separate researchers. Our study shows stage-specific genes and biological processes that may be important in antimalarial drug research efforts. In addition, timed-coordinated control of separate processes may explain the paucity of factors in parasites.

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Transcriptome Analysis Reveals Candidate Genes During the Prepupal-pupal Transition in the Oriental Armyworm, Mythimna separata (Walker) (Lepidoptera: Noctuidae)

10.21203/rs.3.rs-46182/v1 ◽

2020 ◽

Author(s):

Peirong Li ◽

Xinru Li ◽

Wei Wang ◽

Xiaoling Tan ◽

Xiaoqi Wang ◽

...

Keyword(s):

Developmental Stages ◽

Transcriptome Assembly ◽

Insect Pest ◽

Pupal Stage ◽

Differentially Expressed ◽

Biological Processes ◽

Rna Seq ◽

Mythimna Separata ◽

Expression Levels ◽

Lepidoptera Noctuidae

Abstract Background Metamorphosis ensures the transformation of a larva of the holometabolous insects into a reproductive adult through a transitory pupal stage. Understanding how changes in expression levels of genes during the prepupal-pupal transition will inform us of how the metamorphosis arises. Results In this study, mature larvae (ML), wandering (W), 1 day (P1), 5 days (P5), and 10 days (P10) after pupation of the Mythimna separata (Walker), a notorious migratory pest of agricultural crops, were selected, forming five groups. RNA-Seq revealed that the draft transcriptome assembly contained 140562 contigs, and more than half (74,059) were similar to sequence at NCBI (e value < e− 3), including 22884, 23534, 26643, and 33238 differentially expressed genes (DEGs) in ML vs W, W vs P1, P1 vs P5, and P5-vs-P10, respectively. Comparative transcriptomics revealed the enrichment of biological processes related to the membrane and integral component of membrane, which includes the cuticular protein (CP), 20-hydroxyecdysone (20E), and juvenile hormone (JH) biosynthesis, enabled us to delineate and partially validate the metabolic pathway in M. separata. Of these DEGs, 33 CP, 18 20E, and 7 JH genes were differentially expressed across the developmental stages. Correlation analysis uncovered that the relative expression levels of 10 selected CP, 20E, and JH-related genes obtained by real-time PCR quantitative (RT-qPCR) matched well with their FPKM values derived from RNA-seq. Conclusions The data gave here represent an important first step to uncover the molecular mechanism of metamorphosis in M. separata, which also provide valuable information for manipulation of insect development and metamorphosis using the obtained DEGs as targets and broaden the applications of available tools for insect pest control.

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CCPE: Cell Cycle Pseudotime Estimation for Single Cell RNA-seq Data

10.1101/2021.06.13.448263 ◽

2021 ◽

Author(s):

Jiajia Liu ◽

Mengyuan Yang ◽

Weiling Zhao ◽

Xiaobo Zhou

Keyword(s):

Cell Cycle ◽

Single Cell ◽

Rapid Development ◽

Estimation Method ◽

Accurate Prediction ◽

Cellular Heterogeneity ◽

Marker Genes ◽

Biological Processes ◽

Rna Seq ◽

Cell Fate Decisions

AbstractThe rapid development of single-cell RNA-sequencing (scRNA-seq) technologies makes it possible to characterize cellular heterogeneity by detecting and quantifying transcriptional changes at the single-cell level. Pseudotime analysis enables to characterize the continuous progression of various biological processes, such as cell cycle. Cell cycle plays an important regulatory role in cell fate decisions and differentiation and is also often regarded as a confounder in scRNA-seq data analysis when analyzing the role of other factors on transcriptional regulation. Therefore, accurate prediction of cell cycle pseudotime and identify cell stages are important steps for characterizing the development-related biological processes, identifying important regulatory molecules and promoting the analysis of transcriptional heterogeneity. Here, we develop CCPE, a novel cell cycle pseudotime estimation method to characterize cell cycle timing and determine cell cycle phases from single-cell RNA-seq data. CCPE uses a discriminative helix to characterize the circular process and estimates pseudotime in the cell cycle. We evaluated the model performance based on a variety of simulated and real scRNA-seq datasets. Our results indicate that CCPE is an effective method for cell cycle estimation and competitive in various downstream analyses compared with other existing methods. CCPE successfully identified cell cycle marker genes and is robust to dropout events in scRNA-seq data. CCPE also has excellent performance on small datasets with fewer genes or cells. Accurate prediction of the cell cycle in CCPE effectively contributes to cell cycle effect removal across cell types or conditions.

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Effect of kinetin on the course of cell cycle in successive developmental stages of the antheridial filaments of Chara vulgaris L.

Acta Societatis Botanicorum Poloniae ◽

10.5586/asbp.1982.003 ◽

2014 ◽

Vol 51 (1) ◽

pp. 21-37 ◽

Cited By ~ 1

Author(s):

Mirosław Godlewski

Keyword(s):

Cell Cycle ◽

Plant Growth ◽

Plant Growth Regulator ◽

Developmental Stages ◽

Thymidine Incorporation ◽

S Phase ◽

Cell Nuclei ◽

Cell Cycles ◽

Chara Vulgaris ◽

Stimulation Of

Effects of kinetin on the course of cell cycle in successive developmental stages of the antheridial filaments of Chara vulgaris L. were investigated. A shortening of the duration of cell cycles has been observed, particularly in initial. and final developmental stages. S phase. shortened in all stages whereas G2 phase+mitosis shortened in early but become longer in late developmental stages of filaments. Incorporation of 14C-adenine into cell nuclei increased after kinetin treatment in 4- and 8-celled filaments whereas that of 3H-phenylalanine increased in 8- and particularly 16-celled ones. This plant growth regulator stimulated also the 3H-thymidine incorporation into cells in studied developmental stages of filaments. The stimulation of radioactive phenylalanine incorporation into nucleus and cytoplasm was stronger in late G2 phase. A participation of cytokinins in the control of cell cycle in relation to process of differentiation of antheridial cells is discussed. A possibility of changes in the cytokinin content in antheridia and antheridial filament cells during their; development has been postulated.

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