scholarly journals Modeling thecis-regulatory modules of genes expressed in developmental stages ofDrosophila melanogaster

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3389 ◽  
Author(s):  
Yosvany López ◽  
Alexis Vandenbon ◽  
Akinao Nose ◽  
Kenta Nakai
Keyword(s):  
Gene Expression ◽  
Developmental Stages ◽  
Expression Profiles ◽  
Regulation Of Gene Expression ◽  
Structural Features ◽  
Extensive Study ◽  
Pairwise Distance ◽  
Sequencing Data ◽  
Binding Motifs ◽  
Promoter Sequences

Because transcription is the first step in the regulation of gene expression, understanding how transcription factors bind to their DNA binding motifs has become absolutely necessary. It has been shown that the promoters of genes with similar expression profiles share common structural patterns. This paper presents an extensive study of the regulatory regions of genes expressed in 24 developmental stages ofDrosophila melanogaster. It proposes the use of a combination of structural features, such as positioning of individual motifs relative to the transcription start site, orientation, pairwise distance between motifs, and presence of motifs anywhere in the promoter for predicting gene expression from structural features of promoter sequences. RNA-sequencing data was utilized to create and validate the 24 models. When genes with high-scoring promoters were compared to those identified by RNA-seq samples, 19 (79.2%) statistically significant models, a number that exceeds previous studies, were obtained. Each model yielded a set of highly informative features, which were used to search for genes with similar biological functions.

scholarly journals Genome-Wide Identification of Soybean ABC Transporters Relate to Aluminum Toxicity

2021 ◽  
Vol 22 (12) ◽  
pp. 6556
Author(s):  
Junjun Huang ◽  
Xiaoyu Li ◽  
Xin Chen ◽  
Yaru Guo ◽  
Weihong Liang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Abc Transporters ◽  
Developmental Stages ◽  
Aluminum Toxicity ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Purifying Selection ◽  
Biotic Stresses ◽  
Genome Wide ◽  
New Germplasm

ATP-binding cassette (ABC) transporter proteins are a gene super-family in plants and play vital roles in growth, development, and response to abiotic and biotic stresses. The ABC transporters have been identified in crop plants such as rice and buckwheat, but little is known about them in soybean. Soybean is an important oil crop and is one of the five major crops in the world. In this study, 255 ABC genes that putatively encode ABC transporters were identified from soybean through bioinformatics and then categorized into eight subfamilies, including 7 ABCAs, 52 ABCBs, 48 ABCCs, 5 ABCDs, 1 ABCEs, 10 ABCFs, 111 ABCGs, and 21 ABCIs. Their phylogenetic relationships, gene structure, and gene expression profiles were characterized. Segmental duplication was the main reason for the expansion of the GmABC genes. Ka/Ks analysis suggested that intense purifying selection was accompanied by the evolution of GmABC genes. The genome-wide collinearity of soybean with other species showed that GmABCs were relatively conserved and that collinear ABCs between species may have originated from the same ancestor. Gene expression analysis of GmABCs revealed the distinct expression pattern in different tissues and diverse developmental stages. The candidate genes GmABCB23, GmABCB25, GmABCB48, GmABCB52, GmABCI1, GmABCI5, and GmABCI13 were responsive to Al toxicity. This work on the GmABC gene family provides useful information for future studies on ABC transporters in soybean and potential targets for the cultivation of new germplasm resources of aluminum-tolerant soybean.

scholarly journals LncGSEA: a versatile tool to infer lncRNA associated pathways from large-scale cancer transcriptome sequencing data

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yanan Ren ◽  
Ting-You Wang ◽  
Leah C. Anderton ◽  
Qi Cao ◽  
Rendong Yang
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Multiple Cancer ◽  
Regulatory Pathways ◽  
Cancer Transcriptome ◽  
Versatile Tool

Abstract Background Long non-coding RNAs (lncRNAs) are a growing focus in cancer research. Deciphering pathways influenced by lncRNAs is important to understand their role in cancer. Although knock-down or overexpression of lncRNAs followed by gene expression profiling in cancer cell lines are established approaches to address this problem, these experimental data are not available for a majority of the annotated lncRNAs. Results As a surrogate, we present lncGSEA, a convenient tool to predict the lncRNA associated pathways through Gene Set Enrichment Analysis of gene expression profiles from large-scale cancer patient samples. We demonstrate that lncGSEA is able to recapitulate lncRNA associated pathways supported by literature and experimental validations in multiple cancer types. Conclusions LncGSEA allows researchers to infer lncRNA regulatory pathways directly from clinical samples in oncology. LncGSEA is written in R, and is freely accessible at https://github.com/ylab-hi/lncGSEA.

scholarly journals Arginine Methyltransferases as Regulators of RNA-Binding Protein Activities in Pathogenic Kinetoplastids

2021 ◽  
Vol 8 ◽  
Author(s):  
Gustavo D. Campagnaro ◽  
Edward Nay ◽  
Michael J. Plevin ◽  
Angela K. Cruz ◽  
Pegine B. Walrad
Keyword(s):  
Gene Expression ◽  
Transcriptional Control ◽  
Rna Binding ◽  
Methylation Status ◽  
Regulation Of Gene Expression ◽  
Structural Features ◽  
Arginine Methylation ◽  
Diverse Range ◽  
Host Interaction ◽  
Intronless Genes

A large number of eukaryotic proteins are processed by single or combinatorial post-translational covalent modifications that may alter their activity, interactions and fate. The set of modifications of each protein may be considered a “regulatory code”. Among the PTMs, arginine methylation, catalyzed by protein arginine methyltransferases (PRMTs), can affect how a protein interacts with other macromolecules such as nucleic acids or other proteins. In fact, many RNA-binding (RBPs) proteins are targets of PRMTs. The methylation status of RBPs may affect the expression of their bound RNAs and impact a diverse range of physiological and pathological cellular processes. Unlike most eukaryotes, Kinetoplastids have overwhelmingly intronless genes that are arranged within polycistronic units from which mature mRNAs are generated by trans-splicing. Gene expression in these organisms is thus highly dependent on post-transcriptional control, and therefore on the action of RBPs. These genetic features make trypanosomatids excellent models for the study of post-transcriptional regulation of gene expression. The roles of PRMTs in controlling the activity of RBPs in pathogenic kinetoplastids have now been studied for close to 2 decades with important advances achieved in recent years. These include the finding that about 10% of the Trypanosoma brucei proteome carries arginine methylation and that arginine methylation controls Leishmania:host interaction. Herein, we review how trypanosomatid PRMTs regulate the activity of RBPs, including by modulating interactions with RNA and/or protein complex formation, and discuss how this impacts cellular and biological processes. We further highlight unique structural features of trypanosomatid PRMTs and how it contributes to their singular functionality.

scholarly journals Transcriptomic profiles of non-embryogenic and embryogenic callus cells in a highly regenerative Upland Cotton line (Gossypium hirsutum L.)

2020 ◽  
Author(s):  
Li Wen ◽  
Wei Li ◽  
Stephen Parris ◽  
Matthew West ◽  
John Lawson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Somatic Embryogenesis ◽  
Transcription Factors ◽  
Gossypium Hirsutum ◽  
Embryogenic Callus ◽  
Developmental Stages ◽  
Baby Boom ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Study Gene Expression

Abstract • Background • Genotype independent transformation and whole plant regeneration through somatic embryogenesis relies heavily on the intrinsic ability of a genotype to regenerate. • Results • In this study, gene expression profiles of a highly regenerable Gossypium hirsutum L. cultivar, Jin668, were analyzed at two critical developmental stages during somatic embryogenesis, non-embryogenic callus (NEC) cells and embryogenic callus (EC) cells. The rate of EC formation in Jin668 is 96%. Differential gene expression analysis revealed a total of 5,333 differentially expressed genes (DEG) with 2,534 upregulated and 2,799 downregulated in EC. A total of 144 genes were unique to NEC cells and 174 genes unique to EC. Clustering and enrichment analysis identified genes upregulated in EC that function as transcription factors/DNA binding, phytohormone response, oxidative reduction, and regulators of transcription; while genes categorized in methylation pathways were downregulated. Four key transcription factors were identified based on their sharp upregulation in EC tissue; LEAFY COTYLEDON 1 (LEC1), BABY BOOM (BBM), FUSCA (FUS3) and AGAMOUS-LIKE15 with distinguishable subgenome expression bias. • Conclusions • This comparative analysis of NEC and EC transcriptomes gives new insights into the genetic underpinnings of somatic embryogenesis in cotton.

scholarly journals DNA Methylation and RNA-Sequencing Analysis Show Epigenetic Function During Grain Filling in Foxtail Millet (Setaria italica L.)

2021 ◽  
Vol 12 ◽  
Author(s):  
Tao Wang ◽  
Quanwei Lu ◽  
Hui Song ◽  
Nan Hu ◽  
Yangyang Wei ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Potential Function ◽  
Developmental Stages ◽  
Expression Profiles ◽  
Dynamic Change ◽  
Foxtail Millet ◽  
Grain Filling ◽  
Sequencing Analysis ◽  
Grain Development

Grain filling is a crucial process for crop yield and quality. Certain studies already gained insight into the molecular mechanism of grain filling. However, it is unclear whether epigenetic modifications are associated with grain filling in foxtail millet. Global DNA methylation and transcriptome analysis were conducted in foxtail millet spikelets during different stages to interpret the epigenetic effects of the grain filling process. The study employed the whole-genome bisulfite deep sequencing and advanced bioinformatics to sequence and identify all DNA methylation during foxtail millet grain filling; the DNA methylation-mediated gene expression profiles and their involved gene network and biological pathway were systematically studied. One context of DNA methylation, namely, CHH methylation, was accounted for the largest percentage, and it was gradually increased during grain filling. Among all developmental stages, the methylation levels were lowest at T2, followed by T4, which mainly occurred in CHG. The distribution of differentially methylated regions (DMR) was varied in the different genetic regions for three contexts. In addition, gene expression was negatively associated with DNA methylation. Evaluation of the interconnection of the DNA methylome and transcriptome identified some stage-specific differentially expressed genes associated with the DMR at different stages compared with the T1 developmental stage, indicating the potential function of epigenetics on the expression regulation of genes related to the specific pathway at different stages of grain development. The results demonstrated that the dynamic change of DNA methylation plays a crucial function in gene regulation, revealing the potential function of epigenetics in grain development in foxtail millet.

scholarly journals Genetic and epigenetic architecture of sex-biased expression in the jewel wasps Nasonia vitripennis and giraulti

2015 ◽  
Vol 112 (27) ◽  
pp. E3545-E3554 ◽  
Author(s):  
Xu Wang ◽  
John H. Werren ◽  
Andrew G. Clark
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Regulation Of Gene Expression ◽  
Sequence Divergence ◽  
Adult Males ◽  
Rna Seq ◽  
Functional Categories ◽  
Nasonia Vitripennis ◽  
Constitutive Gene Expression ◽  
Genome Bisulfite Sequencing

There is extraordinary diversity in sexual dimorphism (SD) among animals, but little is known about its epigenetic basis. To study the epigenetic architecture of SD in a haplodiploid system, we performed RNA-seq and whole-genome bisulfite sequencing of adult females and males from two closely related parasitoid wasps, Nasonia vitripennis and Nasonia giraulti. More than 75% of expressed genes displayed significantly sex-biased expression. As a consequence, expression profiles are more similar between species within each sex than between sexes within each species. Furthermore, extremely male- and female-biased genes are enriched for totally different functional categories: male-biased genes for key enzymes in sex-pheromone synthesis and female-biased genes for genes involved in epigenetic regulation of gene expression. Remarkably, just 70 highly expressed, extremely male-biased genes account for 10% of all transcripts in adult males. Unlike expression profiles, DNA methylomes are highly similar between sexes within species, with no consistent sex differences in methylation found. Therefore, methylation changes cannot explain the extensive level of sex-biased gene expression observed. Female-biased genes have smaller sequence divergence between species, higher conservation to other hymenopterans, and a broader expression range across development. Overall, female-biased genes have been recruited from genes with more conserved and broadly expressing “house-keeping” functions, whereas male-biased genes are more recently evolved and are predominately testis specific. In summary, Nasonia accomplish a striking degree of sex-biased expression without sex chromosomes or epigenetic differences in methylation. We propose that methylation provides a general signal for constitutive gene expression, whereas other sex-specific signals cause sex-biased gene expression.

scholarly journals Transcriptomic profiles of non-embryogenic and embryogenic callus cells in a highly regenerative upland cotton line (Gossypium hirsutum L.)

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Li Wen ◽  
Wei Li ◽  
Stephen Parris ◽  
Matthew West ◽  
John Lawson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Somatic Embryogenesis ◽  
Transcription Factors ◽  
Gossypium Hirsutum ◽  
Embryogenic Callus ◽  
Developmental Stages ◽  
Baby Boom ◽  
Expression Profiles ◽  
Study Gene Expression ◽  
Ec Cells

Abstract Background Genotype independent transformation and whole plant regeneration through somatic embryogenesis relies heavily on the intrinsic ability of a genotype to regenerate. The critical genetic architecture of non-embryogenic callus (NEC) cells and embryogenic callus (EC) cells in a highly regenerable cotton genotype is unknown. Results In this study, gene expression profiles of a highly regenerable Gossypium hirsutum L. cultivar, Jin668, were analyzed at two critical developmental stages during somatic embryogenesis, non-embryogenic callus (NEC) cells and embryogenic callus (EC) cells. The rate of EC formation in Jin668 is 96%. Differential gene expression analysis revealed a total of 5333 differentially expressed genes (DEG) with 2534 genes upregulated and 2799 genes downregulated in EC. A total of 144 genes were unique to NEC cells and 174 genes were unique to EC. Clustering and enrichment analysis identified genes upregulated in EC that function as transcription factors/DNA binding, phytohormone response, oxidative reduction, and regulators of transcription; while genes categorized in methylation pathways were downregulated. Four key transcription factors were identified based on their sharp upregulation in EC tissue; LEAFY COTYLEDON 1 (LEC1), BABY BOOM (BBM), FUSCA (FUS3) and AGAMOUS-LIKE15 with distinguishable subgenome expression bias. Conclusions This comparative analysis of NEC and EC transcriptomes gives new insights into the genes involved in somatic embryogenesis in cotton.

scholarly journals Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression

2019 ◽  
Vol 116 (39) ◽  
pp. 19490-19499 ◽  
Author(s):  
Chenglong Xia ◽  
Jean Fan ◽  
George Emanuel ◽  
Junjie Hao ◽  
Xiaowei Zhuang
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Spatial Information ◽  
Detection Efficiency ◽  
Expression Profiles ◽  
Regulation Of Gene Expression ◽  
Rna Profiling ◽  
Spatially Resolved ◽  
Cycle Dependent

The expression profiles and spatial distributions of RNAs regulate many cellular functions. Image-based transcriptomic approaches provide powerful means to measure both expression and spatial information of RNAs in individual cells within their native environment. Among these approaches, multiplexed error-robust fluorescence in situ hybridization (MERFISH) has achieved spatially resolved RNA quantification at transcriptome scale by massively multiplexing single-molecule FISH measurements. Here, we increased the gene throughput of MERFISH and demonstrated simultaneous measurements of RNA transcripts from ∼10,000 genes in individual cells with ∼80% detection efficiency and ∼4% misidentification rate. We combined MERFISH with cellular structure imaging to determine subcellular compartmentalization of RNAs. We validated this approach by showing enrichment of secretome transcripts at the endoplasmic reticulum, and further revealed enrichment of long noncoding RNAs, RNAs with retained introns, and a subgroup of protein-coding mRNAs in the cell nucleus. Leveraging spatially resolved RNA profiling, we developed an approach to determine RNA velocity in situ using the balance of nuclear versus cytoplasmic RNA counts. We applied this approach to infer pseudotime ordering of cells and identified cells at different cell-cycle states, revealing ∼1,600 genes with putative cell cycle-dependent expression and a gradual transcription profile change as cells progress through cell-cycle stages. Our analysis further revealed cell cycle-dependent and cell cycle-independent spatial heterogeneity of transcriptionally distinct cells. We envision that the ability to perform spatially resolved, genome-wide RNA profiling with high detection efficiency and accuracy by MERFISH could help address a wide array of questions ranging from the regulation of gene expression in cells to the development of cell fate and organization in tissues.

scholarly journals M3S: a comprehensive model selection for multi-modal single-cell RNA sequencing data

2019 ◽  
Vol 20 (S24) ◽  
Author(s):  
Yu Zhang ◽  
Changlin Wan ◽  
Pengcheng Wang ◽  
Wennan Chang ◽  
Yan Huo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Model Selection ◽  
Statistical Model ◽  
Single Cell ◽  
Differential Gene Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Sequencing Data ◽  
Differential Gene ◽  
Selection Of

Abstract Background Various statistical models have been developed to model the single cell RNA-seq expression profiles, capture its multimodality, and conduct differential gene expression test. However, for expression data generated by different experimental design and platforms, there is currently lack of capability to determine the most proper statistical model. Results We developed an R package, namely Multi-Modal Model Selection (M3S), for gene-wise selection of the most proper multi-modality statistical model and downstream analysis, useful in a single-cell or large scale bulk tissue transcriptomic data. M3S is featured with (1) gene-wise selection of the most parsimonious model among 11 most commonly utilized ones, that can best fit the expression distribution of the gene, (2) parameter estimation of a selected model, and (3) differential gene expression test based on the selected model. Conclusion A comprehensive evaluation suggested that M3S can accurately capture the multimodality on simulated and real single cell data. An open source package and is available through GitHub at https://github.com/zy26/M3S.

scholarly journals The effects of a globin blocker on the resolution of 3’mRNA sequencing data in porcine blood

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Kyu-Sang Lim ◽  
Qian Dong ◽  
Pamela Moll ◽  
Jana Vitkovska ◽  
Gregor Wiktorin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Data Sets ◽  
Globin Genes ◽  
Sequencing Data ◽  
Globin Mrna ◽  
Data Set ◽  
Mrna Sequencing ◽  
Porcine Blood

Abstract Background Gene expression profiling in blood is a potential source of biomarkers to evaluate or predict phenotypic differences between pigs but is expensive and inefficient because of the high abundance of globin mRNA in porcine blood. These limitations can be overcome by the use of QuantSeq 3’mRNA sequencing (QuantSeq) combined with a method to deplete or block the processing of globin mRNA prior to or during library construction. Here, we validated the effectiveness of QuantSeq using a novel specific globin blocker (GB) that is included in the library preparation step of QuantSeq. Results In data set 1, four concentrations of the GB were applied to RNA samples from two pigs. The GB significantly reduced the proportion of globin reads compared to non-GB (NGB) samples (P = 0.005) and increased the number of detectable non-globin genes. The highest evaluated concentration (C1) of the GB resulted in the largest reduction of globin reads compared to the NGB (from 56.4 to 10.1%). The second highest concentration C2, which showed very similar globin depletion rates (12%) as C1 but a better correlation of the expression of non-globin genes between NGB and GB (r = 0.98), allowed the expression of an additional 1295 non-globin genes to be detected, although 40 genes that were detected in the NGB sample (at a low level) were not present in the GB library. Concentration C2 was applied in the rest of the study. In data set 2, the distribution of the percentage of globin reads for NGB (n = 184) and GB (n = 189) samples clearly showed the effects of the GB on reducing globin reads, in particular for HBB, similar to results from data set 1. Data set 3 (n = 84) revealed that the proportion of globin reads that remained in GB samples was significantly and positively correlated with the reticulocyte count in the original blood sample (P < 0.001). Conclusions The effect of the GB on reducing the proportion of globin reads in porcine blood QuantSeq was demonstrated in three data sets. In addition to increasing the efficiency of sequencing non-globin mRNA, the GB for QuantSeq has an advantage that it does not require an additional step prior to or during library creation. Therefore, the GB is a useful tool in the quantification of whole gene expression profiles in porcine blood.

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