scholarly journals Genome-Wide Survey and Expression Analysis of the KT/HAK/KUP Family in Brassica napus and Its Potential Roles in the Response to K+ Deficiency

2020 ◽  
Vol 21 (24) ◽  
pp. 9487
Author(s):  
Jie Zhou ◽  
Hong-Jun Zhou ◽  
Ping Chen ◽  
Lan-Lan Zhang ◽  
Jia-Tian Zhu ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Rna Sequencing ◽  
Expression Profiles ◽  
Small Scale ◽  
Sequencing Data ◽  
Element Analysis ◽  
Transporter Family ◽  
Group I ◽  
Large Expansion ◽  
K Deficiency

The KT/HAK/KUP (HAK) family is the largest potassium (K+) transporter family in plants, which plays key roles in K+ uptake and homeostasis, stress resistance, and root and embryo development. However, the HAK family has not yet been characterized in Brassica napus. In this study, 40 putative B. napus HAK genes (BnaHAKs) are identified and divided into four groups (Groups I–III and V) on the basis of phylogenetic analysis. Gene structure analysis revealed 10 conserved intron insertion sites across different groups. Collinearity analysis demonstrated that both allopolyploidization and small-scale duplication events contributed to the large expansion of BnaHAKs. Transcription factor (TF)-binding network construction, cis-element analysis, and microRNA prediction revealed that the expression of BnaHAKs is regulated by multiple factors. Analysis of RNA-sequencing data further revealed extensive expression profiles of the BnaHAKs in groups II, III, and V, with limited expression in group I. Compared with group I, most of the BnaHAKs in groups II, III, and V were more upregulated by hormone induction based on RNA-sequencing data. Reverse transcription-quantitative polymerase reaction analysis revealed that the expression of eight BnaHAKs of groups I and V was markedly upregulated under K+-deficiency treatment. Collectively, our results provide valuable information and key candidate genes for further functional studies of BnaHAKs.

scholarly journals Global Survey and Expressions of the Phosphate Transporter Gene Families in Brassica napus and Their Roles in Phosphorus Response

2020 ◽  
Vol 21 (5) ◽  
pp. 1752 ◽  
Author(s):  
Jin Yang ◽  
Jie Zhou ◽  
Hong-Jun Zhou ◽  
Mang-Mang Wang ◽  
Ming-Ming Liu ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Expression Profiles ◽  
Phylogenetic Analyses ◽  
Functional Divergence ◽  
Gene Families ◽  
Small Scale ◽  
Transporter Gene ◽  
Promoter Regions ◽  
Network Analyses ◽  
Group I

Phosphate (Pi) transporters play critical roles in Pi acquisition and homeostasis. However, currently little is known about these genes in oil crops. In this study, we aimed to characterize the five Pi transporter gene families (PHT1-5) in allotetraploid Brassica napus. We identified and characterized 81 putative PHT genes in B. napus (BnaPHTs), including 45 genes in PHT1 family (BnaPHT1s), four BnaPHT2s, 10 BnaPHT3s, 13 BnaPHT4s and nine BnaPHT5s. Phylogenetic analyses showed that the largest PHT1 family could be divided into two groups (Group I and II), while PHT4 may be classified into five, Groups I-V. Gene structure analysis revealed that the exon-intron pattern was conservative within the same family or group. The sequence characteristics of these five families were quite different, which may contribute to their functional divergence. Transcription factor (TF) binding network analyses identified many potential TF binding sites in the promoter regions of candidates, implying their possible regulating patterns. Collinearity analysis demonstrated that most BnaPHTs were derived from an allopolyploidization event (~40.7%) between Brassica rapa and Brassica oleracea ancestors, and small-scale segmental duplication events (~39.5%) in the descendant. RNA-Seq analyses proved that many BnaPHTs were preferentially expressed in leaf and flower tissues. The expression profiles of most colinearity-pairs in B. napus are highly correlated, implying functional redundancy, while a few pairs may have undergone neo-functionalization or sub-functionalization during evolution. The expression levels of many BnaPHTs tend to be up-regulated by different hormones inductions, especially for IAA, ABA and 6-BA treatments. qRT-PCR assay demonstrated that six BnaPHT1s (BnaPHT1.11, BnaPHT1.14, BnaPHT1.20, BnaPHT1.35, BnaPHT1.41, BnaPHT1.44) were significantly up-regulated under low- and/or rich- Pi conditions in B. napus roots. This work analyzes the evolution and expression of the PHT family in Brassica napus, which will help further research on their role in Pi transport.

scholarly journals In-depth transcriptomic analysis of human retina reveals molecular mechanisms underlying diabetic retinopathy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kolja Becker ◽  
Holger Klein ◽  
Eric Simon ◽  
Coralie Viollet ◽  
Christian Haslinger ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Rna Sequencing ◽  
Molecular Mechanisms ◽  
Vision Loss ◽  
Ganglion Cells ◽  
Expression Profiles ◽  
Cell Types ◽  
Sequencing Data ◽  
Disease Stages ◽  
Post Transcriptional Regulation

AbstractDiabetic Retinopathy (DR) is among the major global causes for vision loss. With the rise in diabetes prevalence, an increase in DR incidence is expected. Current understanding of both the molecular etiology and pathways involved in the initiation and progression of DR is limited. Via RNA-Sequencing, we analyzed mRNA and miRNA expression profiles of 80 human post-mortem retinal samples from 43 patients diagnosed with various stages of DR. We found differentially expressed transcripts to be predominantly associated with late stage DR and pathways such as hippo and gap junction signaling. A multivariate regression model identified transcripts with progressive changes throughout disease stages, which in turn displayed significant overlap with sphingolipid and cGMP–PKG signaling. Combined analysis of miRNA and mRNA expression further uncovered disease-relevant miRNA/mRNA associations as potential mechanisms of post-transcriptional regulation. Finally, integrating human retinal single cell RNA-Sequencing data revealed a continuous loss of retinal ganglion cells, and Müller cell mediated changes in histidine and β-alanine signaling. While previously considered primarily a vascular disease, attention in DR has shifted to additional mechanisms and cell-types. Our findings offer an unprecedented and unbiased insight into molecular pathways and cell-specific changes in the development of DR, and provide potential avenues for future therapeutic intervention.

scholarly journals COVID-19 Severity Potentially Modulated by Cardiovascular-Disease-Associated Immune Dysregulation

Viruses ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1018
Author(s):  
Abby C. Lee ◽  
Grant Castaneda ◽  
Wei Tse Li ◽  
Chengyu Chen ◽  
Neil Shende ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Mononuclear Cells ◽  
Human Peripheral Blood ◽  
Expression Profiles ◽  
Immune Dysregulation ◽  
Left Ventricular ◽  
Recurrent Event ◽  
Healthy Controls ◽  
Sequencing Data ◽  
Peripheral Blood Mononuclear

Patients with underlying cardiovascular conditions are particularly vulnerable to severe COVID-19. In this project, we aimed to characterize similarities in dysregulated immune pathways between COVID-19 patients and patients with cardiomyopathy, venous thromboembolism (VTE), or coronary artery disease (CAD). We hypothesized that these similarly dysregulated pathways may be critical to how cardiovascular diseases (CVDs) exacerbate COVID-19. To evaluate immune dysregulation in different diseases, we used four separate datasets, including RNA-sequencing data from human left ventricular cardiac muscle samples of patients with dilated or ischemic cardiomyopathy and healthy controls; RNA-sequencing data of whole blood samples from patients with single or recurrent event VTE and healthy controls; RNA-sequencing data of human peripheral blood mononuclear cells (PBMCs) from patients with and without obstructive CAD; and RNA-sequencing data of platelets from COVID-19 subjects and healthy controls. We found similar immune dysregulation profiles between patients with CVDs and COVID-19 patients. Interestingly, cardiomyopathy patients display the most similar immune landscape to COVID-19 patients. Additionally, COVID-19 patients experience greater upregulation of cytokine- and inflammasome-related genes than patients with CVDs. In all, patients with CVDs have a significant overlap of cytokine- and inflammasome-related gene expression profiles with that of COVID-19 patients, possibly explaining their greater vulnerability to severe COVID-19.

scholarly journals A map of tumor–host interactions in glioma at single-cell resolution

GigaScience ◽  
2020 ◽  
Vol 9 (10) ◽  
Author(s):  
Francesca Pia Caruso ◽  
Luciano Garofano ◽  
Fulvio D'Angelo ◽  
Kai Yu ◽  
Fuchou Tang ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cross Talk ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Sequencing Data ◽  
Host Interaction ◽  
Receptor Interactions ◽  
Single Cell Rna Sequencing

ABSTRACT Background Single-cell RNA sequencing is the reference technique for characterizing the heterogeneity of the tumor microenvironment. The composition of the various cell types making up the microenvironment can significantly affect the way in which the immune system activates cancer rejection mechanisms. Understanding the cross-talk signals between immune cells and cancer cells is of fundamental importance for the identification of immuno-oncology therapeutic targets. Results We present a novel method, single-cell Tumor–Host Interaction tool (scTHI), to identify significantly activated ligand–receptor interactions across clusters of cells from single-cell RNA sequencing data. We apply our approach to uncover the ligand–receptor interactions in glioma using 6 publicly available human glioma datasets encompassing 57,060 gene expression profiles from 71 patients. By leveraging this large-scale collection we show that unexpected cross-talk partners are highly conserved across different datasets in the majority of the tumor samples. This suggests that shared cross-talk mechanisms exist in glioma. Conclusions Our results provide a complete map of the active tumor–host interaction pairs in glioma that can be therapeutically exploited to reduce the immunosuppressive action of the microenvironment in brain tumor.

scholarly journals G2S3: a gene graph-based imputation method for single-cell RNA sequencing data

2020 ◽  
Author(s):  
Weimiao Wu ◽  
Qile Dai ◽  
Yunqing Liu ◽  
Xiting Yan ◽  
Zuoheng Wang
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Sequencing Data ◽  
High Data ◽  
Study Gene Expression ◽  
Single Cell Rna Sequencing ◽  
Novel Method

AbstractSingle-cell RNA sequencing provides an opportunity to study gene expression at single-cell resolution. However, prevalent dropout events result in high data sparsity and noise that may obscure downstream analyses. We propose a novel method, G2S3, that imputes dropouts by borrowing information from adjacent genes in a sparse gene graph learned from gene expression profiles across cells. We applied G2S3 and other existing methods to seven single-cell datasets to compare their performance. Our results demonstrated that G2S3 is superior in recovering true expression levels, identifying cell subtypes, improving differential expression analyses, and recovering gene regulatory relationships, especially for mildly expressed genes.

scholarly journals Genome-wide characterization, expression analyses, and functional prediction of the NPF family in Brassica napus

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Jing Wen ◽  
Peng-Feng Li ◽  
Feng Ran ◽  
Peng-Cheng Guo ◽  
Jia-Tian Zhu ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Protein Structures ◽  
Small Scale ◽  
Preferential Expression ◽  
Qrt Pcr ◽  
Genome Wide ◽  
Duplication Events ◽  
Small Scale Duplication

Abstract Background NITRATE TRANSPORTER 1/PEPTIDE TRANSPORTER (NRT1/PTR) family (NPF) members are essential transporters for many substrates in plants, including nitrate, hormones, peptides, and secondary metabolites. Here, we report the global characterization of NPF in the important oil crop Brassica napus, including that for phylogeny, gene/protein structures, duplications, and expression patterns. Results A total of 199 B. napus (BnaNPFs) NPF-coding genes were identified. Phylogenetic analyses categorized these genes into 11 subfamilies, including three new ones. Sequence feature analysis revealed that members of each subfamily contain conserved gene and protein structures. Many hormone−/abiotic stress-responsive cis-acting elements and transcription factor binding sites were identified in BnaNPF promoter regions. Chromosome distribution analysis indicated that BnaNPFs within a subfamily tend to cluster on one chromosome. Syntenic relationship analysis showed that allotetraploid creation by its ancestors (Brassica rapa and Brassica oleracea) (57.89%) and small-scale duplication events (39.85%) contributed to rapid BnaNPF expansion in B. napus. A genome-wide spatiotemporal expression survey showed that NPF genes of each Arabidopsis and B. napus subfamily have preferential expression patterns across developmental stages, most of them are expressed in a few organs. RNA-seq analysis showed that many BnaNPFs (32.66%) have wide exogenous hormone-inductive profiles, suggesting important hormone-mediated patterns in diverse bioprocesses. Homologs in a clade or branch within a given subfamily have conserved organ/spatiotemporal and hormone-inductive profiles, indicating functional conservation during evolution. qRT-PCR-based comparative expression analysis of the 12 BnaNPFs in the NPF2–1 subfamily between high- and low-glucosinolate (GLS) content B. napus varieties revealed that homologs of AtNPF2.9 (BnaNPF2.12, BnaNPF2.13, and BnaNPF2.14), AtNPF2.10 (BnaNPF2.19 and BnaNPF2.20), and AtNPF2.11 (BnaNPF2.26 and BnaNPF2.28) might be involved in GLS transport. qRT-PCR further confirmed the hormone-responsive expression profiles of these putative GLS transporter genes. Conclusion We identified 199 B. napus BnaNPFs; these were divided into 11 subfamilies. Allopolyploidy and small-scale duplication events contributed to the immense expansion of BnaNPFs in B. napus. The BnaNPFs had preferential expression patterns in different tissues/organs and wide hormone-induced expression profiles. Four BnaNPFs in the NPF2–1 subfamily may be involved in GLS transport. Our results provide an abundant gene resource for further functional analysis of BnaNPFs.

scholarly journals Comprehensive analysis of human small RNA sequencing data provides insights into expression profiles and miRNA editing

RNA Biology ◽  
2014 ◽  
Vol 11 (11) ◽  
pp. 1375-1385 ◽  
Author(s):  
Jing Gong ◽  
Yuliang Wu ◽  
Xiantong Zhang ◽  
Yifang Liao ◽  
Vusumuzi Leroy Sibanda ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Small Rna ◽  
Expression Profiles ◽  
Comprehensive Analysis ◽  
Small Rna Sequencing ◽  
Sequencing Data ◽  
Mirna Editing

scholarly journals SoupX removes ambient RNA contamination from droplet based single-cell RNA sequencing data

2018 ◽  
Author(s):  
Matthew D Young ◽  
Sam Behjati
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Expression Profiles ◽  
List Type ◽  
Sequencing Data ◽  
Sequencing Technologies ◽  
Single Cell Rna Sequencing ◽  
Biological Interpretation ◽  
Downstream Analysis ◽  
Rna Contamination

AbstractBackgroundDroplet based single-cell RNA sequence analyses assume all acquired RNAs are endogenous to cells. However, any cell free RNAs contained within the input solution are also captured by these assays. This sequencing of cell free RNA constitutes a background contamination that confounds the biological interpretation of single-cell transcriptomic data.ResultsWe demonstrate that contamination from this ‘soup’ of cell free RNAs is ubiquitous, with experiment-specific variations in composition and magnitude. We present a method, SoupX, for quantifying the extent of the contamination and estimating ‘background corrected’ cell expression profiles that seamlessly integrate with existing downstream analysis tools. Applying this method to several datasets using multiple droplet sequencing technologies, we demonstrate that its application improves biological interpretation of otherwise misleading data, as well as improving quality control metrics.ConclusionsWe present ‘SoupX’, a tool for removing ambient RNA contamination from droplet based single cell RNA sequencing experiments. This tool has broad applicability and its application can improve the biological utility of existing and future data sets.Key PointsThe signal from droplet based single cell RNA sequencing is ubiquitously contaminated by capture of ambient mRNA.SoupX is a method to quantify the abundance of these ambient mRNAs and remove them.Correcting for ambient mRNA contamination improves biological interpretation.

scholarly journals SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data

GigaScience ◽  
2020 ◽  
Vol 9 (12) ◽  
Author(s):  
Matthew D Young ◽  
Sam Behjati
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Expression Profiles ◽  
Sequencing Data ◽  
Sequencing Technologies ◽  
Single Cell Rna Sequencing ◽  
Biological Interpretation ◽  
Downstream Analysis ◽  
Cell Expression ◽  
Rna Contamination

Abstract Background Droplet-based single-cell RNA sequence analyses assume that all acquired RNAs are endogenous to cells. However, any cell-free RNAs contained within the input solution are also captured by these assays. This sequencing of cell-free RNA constitutes a background contamination that confounds the biological interpretation of single-cell transcriptomic data. Results We demonstrate that contamination from this "soup" of cell-free RNAs is ubiquitous, with experiment-specific variations in composition and magnitude. We present a method, SoupX, for quantifying the extent of the contamination and estimating "background-corrected" cell expression profiles that seamlessly integrate with existing downstream analysis tools. Applying this method to several datasets using multiple droplet sequencing technologies, we demonstrate that its application improves biological interpretation of otherwise misleading data, as well as improving quality control metrics. Conclusions We present SoupX, a tool for removing ambient RNA contamination from droplet-based single-cell RNA sequencing experiments. This tool has broad applicability, and its application can improve the biological utility of existing and future datasets.

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