scholarly journals Time-resolved transcriptome of barley anthers and meiocytes reveals robust and largely stable gene expression changes at meiosis entry

2020 ◽  
Author(s):  
Abdellah Barakate ◽  
Jamie Orr ◽  
Miriam Schreiber ◽  
Isabelle Colas ◽  
Dominika Lewandowska ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Temporal Dynamics ◽  
Transcript Abundance ◽  
Future Research ◽  
Stable Gene ◽  
Rna Seq ◽  
Post Translational Modification ◽  
Time Resolved ◽  
Prophase I

ABSTRACTIn flowering plants, successful germinal cell development and meiotic recombination depend upon a combination of environmental and genetic factors. To gain insights into this specialised reproductive development programme we used short- and long-read RNA-sequencing (RNA-seq) to study the temporal dynamics of transcript abundance in immuno-cytologically staged barley (Hordeum vulgare) anthers and meiocytes. We show that the most significant transcriptional changes occur at the transition from pre-meiosis to leptotene–zygotene, which is followed by largely stable transcript abundance throughout prophase I. Our analysis reveals that the developing anthers and meiocytes are enriched in long non-coding RNAs (lncRNAs) and that entry to meiosis is characterized by their robust and significant down regulation. Intriguingly, only 24% of a collection of putative meiotic gene orthologues showed differential transcript abundance in at least one stage or tissue comparison. Changes in the abundance of numerous transcription factors, representatives of the small RNA processing machinery, and post-translational modification pathways highlight the complexity of the regulatory networks involved. These developmental, time-resolved, and dynamic transcriptomes increase our understanding of anther and meiocyte development and will help guide future research.One sentence summaryAnalysis of RNA-seq data from meiotically staged barley anthers and meiocytes highlights the role of lncRNAs within a complex network of transcriptional and post-transcriptional regulation accompanied by a hiatus in differential gene expression during prophase I.The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantcell.org) is: Robbie Waugh ([email protected])

scholarly journals Barley Anther and Meiocyte Transcriptome Dynamics in Meiotic Prophase I

2021 ◽  
Vol 11 ◽  
Author(s):  
Abdellah Barakate ◽  
Jamie Orr ◽  
Miriam Schreiber ◽  
Isabelle Colas ◽  
Dominika Lewandowska ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Temporal Dynamics ◽  
Development Program ◽  
Transcript Abundance ◽  
Developmental Time ◽  
Time Resolved ◽  
Prophase I ◽  
Long Read ◽  
Transcriptional Changes ◽  
Gene Orthologs

In flowering plants, successful germinal cell development and meiotic recombination depend upon a combination of environmental and genetic factors. To gain insights into this specialized reproductive development program we used short- and long-read RNA-sequencing (RNA-seq) to study the temporal dynamics of transcript abundance in immuno-cytologically staged barley (Hordeum vulgare) anthers and meiocytes. We show that the most significant transcriptional changes in anthers occur at the transition from pre-meiosis to leptotene–zygotene, which is followed by increasingly stable transcript abundance throughout prophase I into metaphase I–tetrad. Our analysis reveals that the pre-meiotic anthers are enriched in long non-coding RNAs (lncRNAs) and that entry to meiosis is characterized by their robust and significant down regulation. Intriguingly, only 24% of a collection of putative meiotic gene orthologs showed differential transcript abundance in at least one stage or tissue comparison. Argonautes, E3 ubiquitin ligases, and lys48 specific de-ubiquitinating enzymes were enriched in prophase I meiocyte samples. These developmental, time-resolved transcriptomes demonstrate remarkable stability in transcript abundance in meiocytes throughout prophase I after the initial and substantial reprogramming at meiosis entry and the complexity of the regulatory networks involved in early meiotic processes.

scholarly journals Zea mays RNA-seq estimated transcript abundances are strongly affected by read mapping bias

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shuhua Zhan ◽  
Cortland Griswold ◽  
Lewis Lukens
Keyword(s):  
Gene Expression ◽  
Zea Mays ◽  
Reference Genome ◽  
Transcript Abundance ◽  
Gene Transcript ◽  
Rna Seq ◽  
Individual Genome ◽  
Abundance Estimates ◽  
Mapping Bias ◽  
Quantify Gene Expression

Abstract Background Genetic variation for gene expression is a source of phenotypic variation for natural and agricultural species. The common approach to map and to quantify gene expression from genetically distinct individuals is to assign their RNA-seq reads to a single reference genome. However, RNA-seq reads from alleles dissimilar to this reference genome may fail to map correctly, causing transcript levels to be underestimated. Presently, the extent of this mapping problem is not clear, particularly in highly diverse species. We investigated if mapping bias occurred and if chromosomal features associated with mapping bias. Zea mays presents a model species to assess these questions, given it has genotypically distinct and well-studied genetic lines. Results In Zea mays, the inbred B73 genome is the standard reference genome and template for RNA-seq read assignments. In the absence of mapping bias, B73 and a second inbred line, Mo17, would each have an approximately equal number of regulatory alleles that increase gene expression. Remarkably, Mo17 had 2–4 times fewer such positively acting alleles than did B73 when RNA-seq reads were aligned to the B73 reference genome. Reciprocally, over one-half of the B73 alleles that increased gene expression were not detected when reads were aligned to the Mo17 genome template. Genes at dissimilar chromosomal ends were strongly affected by mapping bias, and genes at more similar pericentromeric regions were less affected. Biased transcript estimates were higher in untranslated regions and lower in splice junctions. Bias occurred across software and alignment parameters. Conclusions Mapping bias very strongly affects gene transcript abundance estimates in maize, and bias varies across chromosomal features. Individual genome or transcriptome templates are likely necessary for accurate transcript estimation across genetically variable individuals in maize and other species.

scholarly journals Using Single Nucleotide Variations in Single-Cell RNA-Seq to Identify Subpopulations and Genotype-phenotype Linkage

2016 ◽  
Author(s):  
Olivier Poirion ◽  
Xun Zhu ◽  
Travers Ching ◽  
Lana X. Garmire
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Single Cells ◽  
Transcript Abundance ◽  
Rna Seq ◽  
Linear Modeling ◽  
Modeling Framework ◽  
Single Nucleotide ◽  
Single Nucleotide Variations

AbstractDespite its popularity, characterization of subpopulations with transcript abundance is subject to a significant amount of noise. We propose to use effective and expressed nucleotide variations (eeSNVs) from scRNA-seq as alternative features for tumor subpopulation identification. We developed a linear modeling framework, SSrGE, to link eeSNVs associated with gene expression. In all the datasets tested, eeSNVs achieve better accuracies than gene expression for identifying subpopulations. Previously validated cancer-relevant genes are also highly ranked, confirming the significance of the method. Moreover, SSrGE is capable of analyzing coupled DNA-seq and RNA-seq data from the same single cells, demonstrating its value in integrating multi-omics single cell techniques. In summary, SNV features from scRNA-seq data have merits for both subpopulation identification and linkage of genotype-phenotype relationship. The method SSrGE is available at https://github.com/lanagarmire/SSrGE.

scholarly journals ISMARA: Completely automated inference of gene regulatory networks from high-throughput data

2017 ◽  
Author(s):  
Mikhail Pachkov ◽  
Piotr J Balwierz ◽  
Phil Arnold ◽  
Andreas J Gruber ◽  
Mihaela Zavolan ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
Regulatory Networks ◽  
Target Genes ◽  
Chromatin State ◽  
Response Analysis ◽  
Rna Seq ◽  
High Throughput Data ◽  
Micro Rnas ◽  
Gene Regulatory

As the costs of high-throughput measurement technologies continue to fall, experimental approaches in biomedicine are increasingly data intensive and the advent of big data is justifiably seen as holding the promise to transform medicine. However, as data volumes mount, researchers increasingly realize that extracting concrete, reliable, and actionable biological predictions from high-throughput data can be very challenging. Our laboratory has pioneered a number of methods for inferring key gene regulatory interactions from high-throughput data. For example, we developed motif activity response analysis (MARA)[, which models genome-wide gene expression (RNA-Seq, or microarray) and chromatin state (ChIP-Seq) data in terms of comprehensive predictions of regulatory sites for hundreds of mammalian regulators (TFs and micro-RNAs). Using these models, MARA identifies the key regulators driving gene expression and chromatin state changes, the activities of these regulators across the input samples, their target genes, and the sites on the genome through which these regulators act. We recently completely automated MARA in an integrated web-server (ismara.unibas.ch) that allows researchers to analyze their own data by simply uploading RNA-Seq or ChIP-Seq datasets, and provides results in an integrated web interface as well as in downloadable flat form.

scholarly journals Transposable elements contribute to the genomic response to insecticides in Drosophila melanogaster

2020 ◽  
Vol 375 (1795) ◽  
pp. 20190341 ◽  
Author(s):  
Judit Salces-Ortiz ◽  
Carlos Vargas-Chavez ◽  
Lain Guio ◽  
Gabriel E. Rech ◽  
Josefa González
Keyword(s):  
Gene Expression ◽  
Drosophila Melanogaster ◽  
Regulatory Networks ◽  
Regulation Of Gene Expression ◽  
Nucleotide Polymorphisms ◽  
Rna Seq ◽  
Organophosphate Insecticide ◽  
Single Nucleotide ◽  
Insecticide Exposure ◽  
Genomic Response

Most of the genotype–phenotype analyses to date have largely centred attention on single nucleotide polymorphisms. However, transposable element (TE) insertions have arisen as a plausible addition to the study of the genotypic–phenotypic link because of to their role in genome function and evolution. In this work, we investigate the contribution of TE insertions to the regulation of gene expression in response to insecticides. We exposed four Drosophila melanogaster strains to malathion, a commonly used organophosphate insecticide. By combining information from different approaches, including RNA-seq and ATAC-seq, we found that TEs can contribute to the regulation of gene expression under insecticide exposure by rewiring cis -regulatory networks. This article is part of a discussion meeting issue ‘Crossroads between transposons and gene regulation’.

ISOFORM ABUNDANCE INFERENCE PROVIDES A MORE ACCURATE ESTIMATION OF GENE EXPRESSION LEVELS IN RNA-SEQ

2010 ◽  
Vol 08 (supp01) ◽  
pp. 177-192 ◽  
Author(s):  
XI WANG ◽  
ZHENGPENG WU ◽  
XUEGONG ZHANG
Keyword(s):  
Gene Expression ◽  
High Throughput Sequencing ◽  
Transcript Abundance ◽  
Accurate Estimation ◽  
Rna Seq ◽  
Estimation Errors ◽  
Expression Levels ◽  
Or Gene ◽  
Read Distribution ◽  
Gene Expression Levels

Due to its unprecedented high-resolution and detailed information, RNA-seq technology based on next-generation high-throughput sequencing significantly boosts the ability to study transcriptomes. The estimation of genes' transcript abundance levels or gene expression levels has always been an important question in research on the transcriptional regulation and gene functions. On the basis of the concept of Reads Per Kilo-base per Million reads (RPKM), taking the union-intersection genes (UI-based) and summing up inferred isoform abundance (isoform-based) are the two current strategies to estimate gene expression levels, but produce different estimations. In this paper, we made the first attempt to compare the two strategies' performances through a series of simulation studies. Our results showed that the isoform-based method gives not only more accurate estimation but also has less uncertainty than the UI-based strategy. If taking into account the non-uniformity of read distribution, the isoform-based method can further reduce estimation errors. We applied both strategies to real RNA-seq datasets of technical replicates, and found that the isoform-based strategy also displays a better performance. For a more accurate estimation of gene expression levels from RNA-seq data, even if the abundance levels of isoforms are not of interest, it is still better to first infer the isoform abundance and sum them up to get the expression level of a gene as a whole.

scholarly journals The Developmental Transcriptome for Lytechinus variegatus Exhibits Temporally Punctuated Gene Expression Changes

2019 ◽  
Author(s):  
John D. Hogan ◽  
Jessica L. Keenan ◽  
Lingqi Luo ◽  
Dakota Y. Hawkins ◽  
Jonas Ibn-Salem ◽  
...  
Keyword(s):  
Gene Expression ◽  
Larval Development ◽  
Sea Urchin ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Lytechinus Variegatus ◽  
Stable Gene ◽  
Major Transitions ◽  
Gene Regulatory ◽  
Embryonic And Larval Development

AbstractEmbryonic development is arguably the most complex process an organism undergoes during its lifetime, and understanding this complexity is best approached with a systems-level perspective. The sea urchin has become a highly valuable model organism for understanding developmental specification, morphogenesis, and evolution. As a non-chordate deuterostome, the sea urchin occupies an important evolutionary niche between protostomes and vertebrates. Lytechinus variegatus (Lv) is an Atlantic species that has been well studied, and which has provided important insights into signal transduction, patterning, and morphogenetic changes during embryonic and larval development. The Pacific species, Strongylocentrotus purpuratus (Sp), is another well-studied sea urchin, particularly for gene regulatory networks (GRNs) and cis-regulatory analyses. A well-annotated genome and transcriptome for Sp are available, but similar resources have not been developed for Lv. Here, we provide an analysis of the Lv transcriptome at 11 timepoints during embryonic and larval development. The data indicate that the gene regulatory networks that underlie specification are well-conserved among sea urchin species. We show that the major transitions in variation of embryonic transcription divide the developmental time series into four distinct, temporally sequential phases. Our work shows that sea urchin development occurs via sequential intervals of relatively stable gene expression states that are punctuated by abrupt transitions.

scholarly journals 3D chromatin organization changes modulate adipogenesis and osteogenesis

2020 ◽  
Author(s):  
Ruo-Han Hao ◽  
Yan Guo ◽  
Jing Guo ◽  
Yu Rong ◽  
Shi Yao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Fate ◽  
Regulatory Networks ◽  
Human Mesenchymal Stem Cells ◽  
Omics Data ◽  
Cell Fate Determination ◽  
Rna Seq ◽  
Loop Detection ◽  
Before And After ◽  
Novel Targets

AbstractHuman mesenchymal stem cells (hMSCs) can be differentiated into adipocytes and osteoblasts. While the transcriptomic and epigenomic changes during adipogenesis and osteogenesis have been characterized, what happens to the chromatin loops is hardly known. Here we induced hMSCs to adipogenic and osteogenic differentiation, and performed 2 kb resolution Hi-C experiments for loop detection and generated RNA-seq, histone modification ChIP-seq and ATAC-seq data for integrative analysis before and after differentiation. We quantitatively identified differential contact loops and unique loops. After integrating with multi-omics data, we demonstrate that strengthened loops after differentiation are associated with gene expression activation. Specially, unique loops are linked with cell fate determination. We also proposed loop-mediated regulatory networks and identified IRS2 and RUNX2 as being activated by cell-specific loops to facilitate adipocytes and osteoblasts commitment, respectively. These results are expected to help better understand the long-range regulation in controlling hMSC differentiation, and provide novel targets for studying adipocytes and osteoblasts determination.

scholarly journals A 24 h Age Difference Causes Twice as Much Gene Expression Divergence as 100 Generations of Adaptation to a Novel Environment

Genes ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 89 ◽  
Author(s):  
Sheng-Kai Hsu ◽  
Ana Marija Jakšić ◽  
Viola Nolte ◽  
Neda Barghi ◽  
François Mallard ◽  
...  
Keyword(s):  
Gene Expression ◽  
Abiotic Factors ◽  
Transcript Abundance ◽  
Age Difference ◽  
Rna Seq ◽  
Experimental Conditions ◽  
Gene Expression Analyses ◽  
High Throughput Phenotyping ◽  
Influence Gene Expression ◽  
Developmental Staging

Gene expression profiling is one of the most reliable high-throughput phenotyping methods, allowing researchers to quantify the transcript abundance of expressed genes. Because many biotic and abiotic factors influence gene expression, it is recommended to control them as tightly as possible. Here, we show that a 24 h age difference of Drosophila simulans females that were subjected to RNA sequencing (RNA-Seq) five and six days after eclosure resulted in more than 2000 differentially expressed genes. This is twice the number of genes that changed expression during 100 generations of evolution in a novel hot laboratory environment. Importantly, most of the genes differing in expression due to age introduce false positives or negatives if an adaptive gene expression analysis is not controlled for age. Our results indicate that tightly controlled experimental conditions, including precise developmental staging, are needed for reliable gene expression analyses, in particular in an evolutionary framework.

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